Overview

Dataset statistics

Number of variables123
Number of observations1448
Missing cells76488
Missing cells (%)42.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 MiB
Average record size in memory8.2 KiB

Variable types

Numeric11
Categorical111
Text1

Alerts

acces_services _ Ville_q2_1 has constant value ""Constant
acces_services _ Ville_q2_2 has constant value ""Constant
acces_services _ Ville_q2_3 has constant value ""Constant
acces_services _ Ville_q2_4 has constant value ""Constant
acces_services _ Ville_q2_5 has constant value ""Constant
acces_services _ Ville_q2_6 has constant value ""Constant
acces_services _ Ville_q2_7 has constant value ""Constant
acces_services _ Ville_q2_8 has constant value ""Constant
acces_services _ Ville_q6_1 has constant value ""Constant
acces_services _ Ville_q6_2 has constant value ""Constant
acces_services _ Ville_q6_3 has constant value ""Constant
acces_services _ Ville_q6_4 has constant value ""Constant
acces_services _ Ville_q6_5 has constant value ""Constant
acces_services _ Ville_q6_6 has constant value ""Constant
acces_services _ Ville_q6_7 has constant value ""Constant
milieu_et_qualite_ de_vie_q10_1 has constant value ""Constant
milieu_et_qualite_de_vie_q10_2 has constant value ""Constant
milieu_et_qualite_ de_vie_q10_3 has constant value ""Constant
milieu_et_qualite_de_vie_q10_4 has constant value ""Constant
milieu_et_qualite_de_vie_q10_5 has constant value ""Constant
milieu_et_qualite_de_vie_q10_6 has constant value ""Constant
milieu_et_qualite_de_vie_q10_7 has constant value ""Constant
milieu_et_qualite_de_vie_q10_8 has constant value ""Constant
milieu_et_qualite_de_vie_q10_9 has constant value ""Constant
securité_dans_espace_public_q14_1 has constant value ""Constant
securité_dans_espace_public_q14_2 has constant value ""Constant
securité_dans_espace_public_q14_3 has constant value ""Constant
securité_dans_espace_public_q14_4 has constant value ""Constant
securité_dans_espace_public_q14_5 has constant value ""Constant
securité_dans_espace_public_q14_6 has constant value ""Constant
securité_dans_espace_public_q14_7 has constant value ""Constant
securité_dans_espace_public_q14_8 has constant value ""Constant
securité_dans_espace_public_q14_9 has constant value ""Constant
securité_dans_espace_public_q14_10 has constant value ""Constant
securité_dans_espace_public_q14_11 has constant value ""Constant
securité_dans_espace_public_q15_1 has constant value ""Constant
securité_dans_espace_public_q15_2 has constant value ""Constant
securité_dans_espace_public_q15_3 has constant value ""Constant
securité_dans_espace_public_q15_4 has constant value ""Constant
securité_dans_espace_public_q15_5 has constant value ""Constant
securité_dans_espace_public_q15_6 has constant value ""Constant
securité_dans_espace_public_q15_7 has constant value ""Constant
securité_dans_espace_public_q15_8 has constant value ""Constant
securité_dans_espace_public_q15_9 has constant value ""Constant
securité_dans_espace_public_q17_1 has constant value ""Constant
securité_dans_espace_public_q17_2 has constant value ""Constant
securité_dans_espace_public_q17_3 has constant value ""Constant
securité_dans_espace_public_q17_4 has constant value ""Constant
securité_dans_espace_public_q17_5 has constant value ""Constant
securité_dans_espace_public_q17_6 has constant value ""Constant
securité_dans_espace_public_q17_7 has constant value ""Constant
securité_dans_espace_public_q17_8 has constant value ""Constant
securité_dans_espace_public_q17_9 has constant value ""Constant
participation_citoyenne_q21_1 has constant value ""Constant
participation_citoyenne_q21_2 has constant value ""Constant
participation_citoyenne_q21_3 has constant value ""Constant
participation_citoyenne_q21_4 has constant value ""Constant
participation_citoyenne_q21_5 has constant value ""Constant
participation_citoyenne_q21_6 has constant value ""Constant
participation_citoyenne_q21_7 has constant value ""Constant
piste_action_q23_1 has constant value ""Constant
piste_action_q23_2 has constant value ""Constant
piste_action_q23_3 has constant value ""Constant
piste_action_q23_4 has constant value ""Constant
piste_action_q23_5 has constant value ""Constant
piste_action_q23_6 has constant value ""Constant
piste_action_q23_7 has constant value ""Constant
piste_action_q23_8 has constant value ""Constant
acces_services _ Ville_q1 is highly overall correlated with acces_services _ Ville_q3High correlation
acces_services _ Ville_q3 is highly overall correlated with acces_services _ Ville_q1High correlation
acces_services _ Ville_q8_2 is highly overall correlated with acces_services _ Ville_q8_3High correlation
acces_services _ Ville_q8_3 is highly overall correlated with acces_services _ Ville_q8_2High correlation
milieu_et_qualite_de_vie_q11_2 is highly overall correlated with milieu_et_qualite_de_vie_q11_3 and 1 other fieldsHigh correlation
milieu_et_qualite_de_vie_q11_3 is highly overall correlated with milieu_et_qualite_de_vie_q11_2 and 1 other fieldsHigh correlation
milieu_et_qualite_de_vie_q11_4 is highly overall correlated with milieu_et_qualite_de_vie_q11_5High correlation
milieu_et_qualite_de_vie_q11_5 is highly overall correlated with milieu_et_qualite_de_vie_q11_2 and 3 other fieldsHigh correlation
milieu_et_qualité_de_vie_q11_6 is highly overall correlated with milieu_et_qualite_de_vie_q11_5High correlation
milieu_et_qualite_de_vie_q11_7 is highly overall correlated with milieu_et_qualite_de_vie_q11_8High correlation
milieu_et_qualite_de_vie_q11_8 is highly overall correlated with milieu_et_qualite_de_vie_q11_7High correlation
securité_dans_espace_public_q16 is highly overall correlated with securité_dans_espace_public_q18High correlation
securité_dans_espace_public_q18 is highly overall correlated with securité_dans_espace_public_q16High correlation
securité_dans_espace_public_q16 is highly imbalanced (55.5%)Imbalance
participation_citoyenne_q20 is highly imbalanced (59.1%)Imbalance
profil_q29 is highly imbalanced (52.4%)Imbalance
profil_q32 is highly imbalanced (75.4%)Imbalance
profil_q35 is highly imbalanced (76.7%)Imbalance
interet_participer_groupe_discussion_q40 is highly imbalanced (60.4%)Imbalance
acces_services _ Ville_q2_1 has 732 (50.6%) missing valuesMissing
acces_services _ Ville_q2_2 has 1115 (77.0%) missing valuesMissing
acces_services _ Ville_q2_3 has 1205 (83.2%) missing valuesMissing
acces_services _ Ville_q2_4 has 1205 (83.2%) missing valuesMissing
acces_services _ Ville_q2_5 has 861 (59.5%) missing valuesMissing
acces_services _ Ville_q2_6 has 459 (31.7%) missing valuesMissing
acces_services _ Ville_q2_7 has 1266 (87.4%) missing valuesMissing
acces_services _ Ville_q2_8 has 1082 (74.7%) missing valuesMissing
acces_services _ Ville_q4 has 94 (6.5%) missing valuesMissing
acces_services _ Ville_q6_1 has 1342 (92.7%) missing valuesMissing
acces_services _ Ville_q6_2 has 1321 (91.2%) missing valuesMissing
acces_services _ Ville_q6_3 has 1356 (93.6%) missing valuesMissing
acces_services _ Ville_q6_4 has 1194 (82.5%) missing valuesMissing
acces_services _ Ville_q6_5 has 1281 (88.5%) missing valuesMissing
acces_services _ Ville_q6_6 has 1376 (95.0%) missing valuesMissing
acces_services _ Ville_q6_7 has 1392 (96.1%) missing valuesMissing
milieu_et_qualite_ de_vie_q10_1 has 1137 (78.5%) missing valuesMissing
milieu_et_qualite_de_vie_q10_2 has 1277 (88.2%) missing valuesMissing
milieu_et_qualite_ de_vie_q10_3 has 1277 (88.2%) missing valuesMissing
milieu_et_qualite_de_vie_q10_4 has 1042 (72.0%) missing valuesMissing
milieu_et_qualite_de_vie_q10_5 has 1220 (84.3%) missing valuesMissing
milieu_et_qualite_de_vie_q10_6 has 1396 (96.4%) missing valuesMissing
milieu_et_qualite_de_vie_q10_7 has 1338 (92.4%) missing valuesMissing
milieu_et_qualite_de_vie_q10_8 has 1172 (80.9%) missing valuesMissing
milieu_et_qualite_de_vie_q10_9 has 752 (51.9%) missing valuesMissing
milieu_et_qualite_de_vie_q11_2 has 31 (2.1%) missing valuesMissing
milieu_et_qualite_de_vie_q11_3 has 37 (2.6%) missing valuesMissing
milieu_et_qualite_de_vie_q11_4 has 37 (2.6%) missing valuesMissing
milieu_et_qualite_de_vie_q11_5 has 38 (2.6%) missing valuesMissing
milieu_et_qualité_de_vie_q11_6 has 42 (2.9%) missing valuesMissing
milieu_et_qualite_de_vie_q11_8 has 22 (1.5%) missing valuesMissing
securité_dans_espace_public_q14_1 has 623 (43.0%) missing valuesMissing
securité_dans_espace_public_q14_2 has 1017 (70.2%) missing valuesMissing
securité_dans_espace_public_q14_3 has 1212 (83.7%) missing valuesMissing
securité_dans_espace_public_q14_4 has 1350 (93.2%) missing valuesMissing
securité_dans_espace_public_q14_5 has 1352 (93.4%) missing valuesMissing
securité_dans_espace_public_q14_6 has 1252 (86.5%) missing valuesMissing
securité_dans_espace_public_q14_7 has 1390 (96.0%) missing valuesMissing
securité_dans_espace_public_q14_8 has 1159 (80.0%) missing valuesMissing
securité_dans_espace_public_q14_9 has 692 (47.8%) missing valuesMissing
securité_dans_espace_public_q14_10 has 1349 (93.2%) missing valuesMissing
securité_dans_espace_public_q14_11 has 1081 (74.7%) missing valuesMissing
securité_dans_espace_public_q15_1 has 831 (57.4%) missing valuesMissing
securité_dans_espace_public_q15_2 has 1380 (95.3%) missing valuesMissing
securité_dans_espace_public_q15_3 has 1411 (97.4%) missing valuesMissing
securité_dans_espace_public_q15_4 has 1319 (91.1%) missing valuesMissing
securité_dans_espace_public_q15_5 has 1076 (74.3%) missing valuesMissing
securité_dans_espace_public_q15_6 has 735 (50.8%) missing valuesMissing
securité_dans_espace_public_q15_7 has 1172 (80.9%) missing valuesMissing
securité_dans_espace_public_q15_8 has 1100 (76.0%) missing valuesMissing
securité_dans_espace_public_q15_9 has 1139 (78.7%) missing valuesMissing
securité_dans_espace_public_q16 has 365 (25.2%) missing valuesMissing
securité_dans_espace_public_q17_1 has 1009 (69.7%) missing valuesMissing
securité_dans_espace_public_q17_2 has 979 (67.6%) missing valuesMissing
securité_dans_espace_public_q17_3 has 1321 (91.2%) missing valuesMissing
securité_dans_espace_public_q17_4 has 1206 (83.3%) missing valuesMissing
securité_dans_espace_public_q17_5 has 1328 (91.7%) missing valuesMissing
securité_dans_espace_public_q17_6 has 1370 (94.6%) missing valuesMissing
securité_dans_espace_public_q17_7 has 913 (63.1%) missing valuesMissing
securité_dans_espace_public_q17_8 has 1017 (70.2%) missing valuesMissing
securité_dans_espace_public_q17_9 has 1415 (97.7%) missing valuesMissing
securité_dans_espace_public_q18 has 1387 (95.8%) missing valuesMissing
participation_citoyenne_q20 has 1131 (78.1%) missing valuesMissing
participation_citoyenne_q21_1 has 1235 (85.3%) missing valuesMissing
participation_citoyenne_q21_2 has 1049 (72.4%) missing valuesMissing
participation_citoyenne_q21_3 has 889 (61.4%) missing valuesMissing
participation_citoyenne_q21_4 has 603 (41.6%) missing valuesMissing
participation_citoyenne_q21_5 has 1003 (69.3%) missing valuesMissing
participation_citoyenne_q21_6 has 1273 (87.9%) missing valuesMissing
participation_citoyenne_q21_7 has 1241 (85.7%) missing valuesMissing
piste_action_q23_1 has 450 (31.1%) missing valuesMissing
piste_action_q23_2 has 583 (40.3%) missing valuesMissing
piste_action_q23_3 has 429 (29.6%) missing valuesMissing
piste_action_q23_4 has 442 (30.5%) missing valuesMissing
piste_action_q23_5 has 514 (35.5%) missing valuesMissing
piste_action_q23_6 has 597 (41.2%) missing valuesMissing
piste_action_q23_7 has 419 (28.9%) missing valuesMissing
piste_action_q23_8 has 648 (44.8%) missing valuesMissing
profil_q37 has 16 (1.1%) missing valuesMissing
interet_participer_groupe_discussion_q40 has 898 (62.0%) missing valuesMissing
id is uniformly distributedUniform
id has unique valuesUnique

Reproduction

Analysis started2023-06-18 04:16:51.253455
Analysis finished2023-06-18 04:18:03.469345
Duration1 minute and 12.22 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct1448
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean724.5
Minimum1
Maximum1448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:18:03.691516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile73.35
Q1362.75
median724.5
Q31086.25
95-th percentile1375.65
Maximum1448
Range1447
Interquartile range (IQR)723.5

Descriptive statistics

Standard deviation418.14591
Coefficient of variation (CV)0.57715101
Kurtosis-1.2
Mean724.5
Median Absolute Deviation (MAD)362
Skewness0
Sum1049076
Variance174846
MonotonicityStrictly increasing
2023-06-18T04:18:04.333343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
973 1
 
0.1%
971 1
 
0.1%
970 1
 
0.1%
969 1
 
0.1%
968 1
 
0.1%
967 1
 
0.1%
966 1
 
0.1%
965 1
 
0.1%
964 1
 
0.1%
Other values (1438) 1438
99.3%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1448 1
0.1%
1447 1
0.1%
1446 1
0.1%
1445 1
0.1%
1444 1
0.1%
1443 1
0.1%
1442 1
0.1%
1441 1
0.1%
1440 1
0.1%
1439 1
0.1%

acces_services _ Ville_q1
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Oui
1216 
Non
232 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui
2nd rowOui
3rd rowOui
4th rowOui
5th rowOui

Common Values

ValueCountFrequency (%)
Oui 1216
84.0%
Non 232
 
16.0%

Length

2023-06-18T04:18:05.257920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:06.016185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 1216
84.0%
non 232
 
16.0%

Most occurring characters

ValueCountFrequency (%)
O 1216
28.0%
u 1216
28.0%
i 1216
28.0%
N 232
 
5.3%
o 232
 
5.3%
n 232
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 1216
42.0%
i 1216
42.0%
o 232
 
8.0%
n 232
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
O 1216
84.0%
N 232
 
16.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 1216
28.0%
u 1216
28.0%
i 1216
28.0%
N 232
 
5.3%
o 232
 
5.3%
n 232
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 1216
28.0%
u 1216
28.0%
i 1216
28.0%
N 232
 
5.3%
o 232
 
5.3%
n 232
 
5.3%

acces_services _ Ville_q2_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing732
Missing (%)50.6%
Memory size121.7 KiB
Bibliothèques municipales
716 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters17900
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBibliothèques municipales
2nd rowBibliothèques municipales
3rd rowBibliothèques municipales
4th rowBibliothèques municipales
5th rowBibliothèques municipales

Common Values

ValueCountFrequency (%)
Bibliothèques municipales 716
49.4%
(Missing) 732
50.6%

Length

2023-06-18T04:18:06.733047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:07.511363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
bibliothèques 716
50.0%
municipales 716
50.0%

Most occurring characters

ValueCountFrequency (%)
i 2864
16.0%
u 1432
 
8.0%
e 1432
 
8.0%
l 1432
 
8.0%
s 1432
 
8.0%
p 716
 
4.0%
c 716
 
4.0%
n 716
 
4.0%
m 716
 
4.0%
716
 
4.0%
Other values (8) 5728
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16468
92.0%
Space Separator 716
 
4.0%
Uppercase Letter 716
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2864
17.4%
u 1432
 
8.7%
e 1432
 
8.7%
l 1432
 
8.7%
s 1432
 
8.7%
p 716
 
4.3%
c 716
 
4.3%
n 716
 
4.3%
m 716
 
4.3%
q 716
 
4.3%
Other values (6) 4296
26.1%
Space Separator
ValueCountFrequency (%)
716
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 716
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17184
96.0%
Common 716
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2864
16.7%
u 1432
 
8.3%
e 1432
 
8.3%
l 1432
 
8.3%
s 1432
 
8.3%
p 716
 
4.2%
c 716
 
4.2%
n 716
 
4.2%
m 716
 
4.2%
B 716
 
4.2%
Other values (7) 5012
29.2%
Common
ValueCountFrequency (%)
716
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17184
96.0%
None 716
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 2864
16.7%
u 1432
 
8.3%
e 1432
 
8.3%
l 1432
 
8.3%
s 1432
 
8.3%
p 716
 
4.2%
c 716
 
4.2%
n 716
 
4.2%
m 716
 
4.2%
716
 
4.2%
Other values (7) 5012
29.2%
None
ValueCountFrequency (%)
è 716
100.0%

acces_services _ Ville_q2_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1115
Missing (%)77.0%
Memory size85.3 KiB
Bureaux Accès Montréal
333 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters7326
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBureaux Accès Montréal
2nd rowBureaux Accès Montréal
3rd rowBureaux Accès Montréal
4th rowBureaux Accès Montréal
5th rowBureaux Accès Montréal

Common Values

ValueCountFrequency (%)
Bureaux Accès Montréal 333
 
23.0%
(Missing) 1115
77.0%

Length

2023-06-18T04:18:08.191829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:08.683554image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
bureaux 333
33.3%
accès 333
33.3%
montréal 333
33.3%

Most occurring characters

ValueCountFrequency (%)
c 666
 
9.1%
r 666
 
9.1%
a 666
 
9.1%
666
 
9.1%
u 666
 
9.1%
M 333
 
4.5%
é 333
 
4.5%
t 333
 
4.5%
n 333
 
4.5%
o 333
 
4.5%
Other values (7) 2331
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5661
77.3%
Uppercase Letter 999
 
13.6%
Space Separator 666
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 666
11.8%
r 666
11.8%
a 666
11.8%
u 666
11.8%
é 333
 
5.9%
t 333
 
5.9%
n 333
 
5.9%
o 333
 
5.9%
s 333
 
5.9%
è 333
 
5.9%
Other values (3) 999
17.6%
Uppercase Letter
ValueCountFrequency (%)
M 333
33.3%
B 333
33.3%
A 333
33.3%
Space Separator
ValueCountFrequency (%)
666
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6660
90.9%
Common 666
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 666
 
10.0%
r 666
 
10.0%
a 666
 
10.0%
u 666
 
10.0%
M 333
 
5.0%
é 333
 
5.0%
t 333
 
5.0%
n 333
 
5.0%
o 333
 
5.0%
B 333
 
5.0%
Other values (6) 1998
30.0%
Common
ValueCountFrequency (%)
666
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6660
90.9%
None 666
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 666
 
10.0%
r 666
 
10.0%
a 666
 
10.0%
666
 
10.0%
u 666
 
10.0%
M 333
 
5.0%
t 333
 
5.0%
n 333
 
5.0%
o 333
 
5.0%
B 333
 
5.0%
Other values (5) 1665
25.0%
None
ValueCountFrequency (%)
é 333
50.0%
è 333
50.0%

acces_services _ Ville_q2_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1205
Missing (%)83.2%
Memory size88.7 KiB
Bureaux Accès culture ou Maisons de la culture
243 

Length

Max length46
Median length46
Mean length46
Min length46

Characters and Unicode

Total characters11178
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBureaux Accès culture ou Maisons de la culture
2nd rowBureaux Accès culture ou Maisons de la culture
3rd rowBureaux Accès culture ou Maisons de la culture
4th rowBureaux Accès culture ou Maisons de la culture
5th rowBureaux Accès culture ou Maisons de la culture

Common Values

ValueCountFrequency (%)
Bureaux Accès culture ou Maisons de la culture 243
 
16.8%
(Missing) 1205
83.2%

Length

2023-06-18T04:18:09.160165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:09.553627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
culture 486
25.0%
bureaux 243
12.5%
accès 243
12.5%
ou 243
12.5%
maisons 243
12.5%
de 243
12.5%
la 243
12.5%

Most occurring characters

ValueCountFrequency (%)
1701
15.2%
u 1701
15.2%
e 972
8.7%
c 972
8.7%
r 729
 
6.5%
a 729
 
6.5%
s 729
 
6.5%
l 729
 
6.5%
t 486
 
4.3%
o 486
 
4.3%
Other values (8) 1944
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8748
78.3%
Space Separator 1701
 
15.2%
Uppercase Letter 729
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 1701
19.4%
e 972
11.1%
c 972
11.1%
r 729
8.3%
a 729
8.3%
s 729
8.3%
l 729
8.3%
t 486
 
5.6%
o 486
 
5.6%
n 243
 
2.8%
Other values (4) 972
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 243
33.3%
M 243
33.3%
A 243
33.3%
Space Separator
ValueCountFrequency (%)
1701
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9477
84.8%
Common 1701
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 1701
17.9%
e 972
10.3%
c 972
10.3%
r 729
7.7%
a 729
7.7%
s 729
7.7%
l 729
7.7%
t 486
 
5.1%
o 486
 
5.1%
B 243
 
2.6%
Other values (7) 1701
17.9%
Common
ValueCountFrequency (%)
1701
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10935
97.8%
None 243
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1701
15.6%
u 1701
15.6%
e 972
8.9%
c 972
8.9%
r 729
6.7%
a 729
6.7%
s 729
6.7%
l 729
6.7%
t 486
 
4.4%
o 486
 
4.4%
Other values (7) 1701
15.6%
None
ValueCountFrequency (%)
è 243
100.0%

acces_services _ Ville_q2_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1205
Missing (%)83.2%
Memory size88.7 KiB
Bureaux Accès culture ou Maisons de la culture
243 

Length

Max length46
Median length46
Mean length46
Min length46

Characters and Unicode

Total characters11178
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBureaux Accès culture ou Maisons de la culture
2nd rowBureaux Accès culture ou Maisons de la culture
3rd rowBureaux Accès culture ou Maisons de la culture
4th rowBureaux Accès culture ou Maisons de la culture
5th rowBureaux Accès culture ou Maisons de la culture

Common Values

ValueCountFrequency (%)
Bureaux Accès culture ou Maisons de la culture 243
 
16.8%
(Missing) 1205
83.2%

Length

2023-06-18T04:18:09.909386image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:10.409764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
culture 486
25.0%
bureaux 243
12.5%
accès 243
12.5%
ou 243
12.5%
maisons 243
12.5%
de 243
12.5%
la 243
12.5%

Most occurring characters

ValueCountFrequency (%)
1701
15.2%
u 1701
15.2%
e 972
8.7%
c 972
8.7%
r 729
 
6.5%
a 729
 
6.5%
s 729
 
6.5%
l 729
 
6.5%
t 486
 
4.3%
o 486
 
4.3%
Other values (8) 1944
17.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8748
78.3%
Space Separator 1701
 
15.2%
Uppercase Letter 729
 
6.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 1701
19.4%
e 972
11.1%
c 972
11.1%
r 729
8.3%
a 729
8.3%
s 729
8.3%
l 729
8.3%
t 486
 
5.6%
o 486
 
5.6%
n 243
 
2.8%
Other values (4) 972
11.1%
Uppercase Letter
ValueCountFrequency (%)
B 243
33.3%
M 243
33.3%
A 243
33.3%
Space Separator
ValueCountFrequency (%)
1701
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9477
84.8%
Common 1701
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 1701
17.9%
e 972
10.3%
c 972
10.3%
r 729
7.7%
a 729
7.7%
s 729
7.7%
l 729
7.7%
t 486
 
5.1%
o 486
 
5.1%
B 243
 
2.6%
Other values (7) 1701
17.9%
Common
ValueCountFrequency (%)
1701
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10935
97.8%
None 243
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1701
15.6%
u 1701
15.6%
e 972
8.9%
c 972
8.9%
r 729
6.7%
a 729
6.7%
s 729
6.7%
l 729
6.7%
t 486
 
4.4%
o 486
 
4.4%
Other values (7) 1701
15.6%
None
ValueCountFrequency (%)
è 243
100.0%

acces_services _ Ville_q2_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing861
Missing (%)59.5%
Memory size104.8 KiB
Centres sportifs et de loisirs (piscines, terrains de tennis, etc.)
587 

Length

Max length67
Median length67
Mean length67
Min length67

Characters and Unicode

Total characters39329
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)
2nd rowCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)
3rd rowCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)
4th rowCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)
5th rowCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)

Common Values

ValueCountFrequency (%)
Centres sportifs et de loisirs (piscines, terrains de tennis, etc.) 587
40.5%
(Missing) 861
59.5%

Length

2023-06-18T04:18:10.785664image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:11.200688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 1174
20.0%
centres 587
10.0%
sportifs 587
10.0%
et 587
10.0%
loisirs 587
10.0%
piscines 587
10.0%
terrains 587
10.0%
tennis 587
10.0%
etc 587
10.0%

Most occurring characters

ValueCountFrequency (%)
s 5283
13.4%
5283
13.4%
e 5283
13.4%
i 4109
10.4%
t 3522
9.0%
n 2935
7.5%
r 2935
7.5%
c 1174
 
3.0%
p 1174
 
3.0%
o 1174
 
3.0%
Other values (9) 6457
16.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30524
77.6%
Space Separator 5283
 
13.4%
Other Punctuation 1761
 
4.5%
Uppercase Letter 587
 
1.5%
Open Punctuation 587
 
1.5%
Close Punctuation 587
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 5283
17.3%
e 5283
17.3%
i 4109
13.5%
t 3522
11.5%
n 2935
9.6%
r 2935
9.6%
c 1174
 
3.8%
p 1174
 
3.8%
o 1174
 
3.8%
d 1174
 
3.8%
Other values (3) 1761
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 1174
66.7%
. 587
33.3%
Space Separator
ValueCountFrequency (%)
5283
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 587
100.0%
Open Punctuation
ValueCountFrequency (%)
( 587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 587
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31111
79.1%
Common 8218
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 5283
17.0%
e 5283
17.0%
i 4109
13.2%
t 3522
11.3%
n 2935
9.4%
r 2935
9.4%
c 1174
 
3.8%
p 1174
 
3.8%
o 1174
 
3.8%
d 1174
 
3.8%
Other values (4) 2348
7.5%
Common
ValueCountFrequency (%)
5283
64.3%
, 1174
 
14.3%
. 587
 
7.1%
( 587
 
7.1%
) 587
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39329
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 5283
13.4%
5283
13.4%
e 5283
13.4%
i 4109
10.4%
t 3522
9.0%
n 2935
7.5%
r 2935
7.5%
c 1174
 
3.0%
p 1174
 
3.0%
o 1174
 
3.0%
Other values (9) 6457
16.4%

acces_services _ Ville_q2_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing459
Missing (%)31.7%
Memory size183.2 KiB
Réseau des parcs de quartier et grands parcs
989 

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters43516
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRéseau des parcs de quartier et grands parcs
2nd rowRéseau des parcs de quartier et grands parcs
3rd rowRéseau des parcs de quartier et grands parcs
4th rowRéseau des parcs de quartier et grands parcs
5th rowRéseau des parcs de quartier et grands parcs

Common Values

ValueCountFrequency (%)
Réseau des parcs de quartier et grands parcs 989
68.3%
(Missing) 459
31.7%

Length

2023-06-18T04:18:11.386235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:11.595809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
parcs 1978
25.0%
réseau 989
12.5%
des 989
12.5%
de 989
12.5%
quartier 989
12.5%
et 989
12.5%
grands 989
12.5%

Most occurring characters

ValueCountFrequency (%)
6923
15.9%
s 4945
11.4%
e 4945
11.4%
a 4945
11.4%
r 4945
11.4%
d 2967
6.8%
u 1978
 
4.5%
p 1978
 
4.5%
c 1978
 
4.5%
t 1978
 
4.5%
Other values (6) 5934
13.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35604
81.8%
Space Separator 6923
 
15.9%
Uppercase Letter 989
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4945
13.9%
e 4945
13.9%
a 4945
13.9%
r 4945
13.9%
d 2967
8.3%
u 1978
 
5.6%
p 1978
 
5.6%
c 1978
 
5.6%
t 1978
 
5.6%
é 989
 
2.8%
Other values (4) 3956
11.1%
Space Separator
ValueCountFrequency (%)
6923
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 989
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36593
84.1%
Common 6923
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4945
13.5%
e 4945
13.5%
a 4945
13.5%
r 4945
13.5%
d 2967
8.1%
u 1978
 
5.4%
p 1978
 
5.4%
c 1978
 
5.4%
t 1978
 
5.4%
R 989
 
2.7%
Other values (5) 4945
13.5%
Common
ValueCountFrequency (%)
6923
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42527
97.7%
None 989
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6923
16.3%
s 4945
11.6%
e 4945
11.6%
a 4945
11.6%
r 4945
11.6%
d 2967
7.0%
u 1978
 
4.7%
p 1978
 
4.7%
c 1978
 
4.7%
t 1978
 
4.7%
Other values (5) 4945
11.6%
None
ValueCountFrequency (%)
é 989
100.0%

acces_services _ Ville_q2_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing1266
Missing (%)87.4%
Memory size63.6 KiB
Jardins communautaires
182 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters4004
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJardins communautaires
2nd rowJardins communautaires
3rd rowJardins communautaires
4th rowJardins communautaires
5th rowJardins communautaires

Common Values

ValueCountFrequency (%)
Jardins communautaires 182
 
12.6%
(Missing) 1266
87.4%

Length

2023-06-18T04:18:11.810144image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:12.047330image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
jardins 182
50.0%
communautaires 182
50.0%

Most occurring characters

ValueCountFrequency (%)
a 546
13.6%
r 364
9.1%
i 364
9.1%
n 364
9.1%
s 364
9.1%
m 364
9.1%
u 364
9.1%
J 182
 
4.5%
d 182
 
4.5%
182
 
4.5%
Other values (4) 728
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3640
90.9%
Uppercase Letter 182
 
4.5%
Space Separator 182
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 546
15.0%
r 364
10.0%
i 364
10.0%
n 364
10.0%
s 364
10.0%
m 364
10.0%
u 364
10.0%
d 182
 
5.0%
c 182
 
5.0%
o 182
 
5.0%
Other values (2) 364
10.0%
Uppercase Letter
ValueCountFrequency (%)
J 182
100.0%
Space Separator
ValueCountFrequency (%)
182
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3822
95.5%
Common 182
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 546
14.3%
r 364
9.5%
i 364
9.5%
n 364
9.5%
s 364
9.5%
m 364
9.5%
u 364
9.5%
J 182
 
4.8%
d 182
 
4.8%
c 182
 
4.8%
Other values (3) 546
14.3%
Common
ValueCountFrequency (%)
182
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 546
13.6%
r 364
9.1%
i 364
9.1%
n 364
9.1%
s 364
9.1%
m 364
9.1%
u 364
9.1%
J 182
 
4.5%
d 182
 
4.5%
182
 
4.5%
Other values (4) 728
18.2%

acces_services _ Ville_q2_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1082
Missing (%)74.7%
Memory size88.1 KiB
Ligne téléphonique 311
366 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters8052
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLigne téléphonique 311
2nd rowLigne téléphonique 311
3rd rowLigne téléphonique 311
4th rowLigne téléphonique 311
5th rowLigne téléphonique 311

Common Values

ValueCountFrequency (%)
Ligne téléphonique 311 366
 
25.3%
(Missing) 1082
74.7%

Length

2023-06-18T04:18:12.247037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:12.482441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ligne 366
33.3%
téléphonique 366
33.3%
311 366
33.3%

Most occurring characters

ValueCountFrequency (%)
i 732
 
9.1%
n 732
 
9.1%
e 732
 
9.1%
732
 
9.1%
é 732
 
9.1%
1 732
 
9.1%
L 366
 
4.5%
g 366
 
4.5%
t 366
 
4.5%
l 366
 
4.5%
Other values (6) 2196
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5856
72.7%
Decimal Number 1098
 
13.6%
Space Separator 732
 
9.1%
Uppercase Letter 366
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 732
12.5%
n 732
12.5%
e 732
12.5%
é 732
12.5%
g 366
6.2%
t 366
6.2%
l 366
6.2%
p 366
6.2%
h 366
6.2%
o 366
6.2%
Other values (2) 732
12.5%
Decimal Number
ValueCountFrequency (%)
1 732
66.7%
3 366
33.3%
Space Separator
ValueCountFrequency (%)
732
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6222
77.3%
Common 1830
 
22.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 732
11.8%
n 732
11.8%
e 732
11.8%
é 732
11.8%
L 366
 
5.9%
g 366
 
5.9%
t 366
 
5.9%
l 366
 
5.9%
p 366
 
5.9%
h 366
 
5.9%
Other values (3) 1098
17.6%
Common
ValueCountFrequency (%)
732
40.0%
1 732
40.0%
3 366
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7320
90.9%
None 732
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 732
 
10.0%
n 732
 
10.0%
e 732
 
10.0%
732
 
10.0%
1 732
 
10.0%
L 366
 
5.0%
g 366
 
5.0%
t 366
 
5.0%
l 366
 
5.0%
p 366
 
5.0%
Other values (5) 1830
25.0%
None
ValueCountFrequency (%)
é 732
100.0%

acces_services _ Ville_q3
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size170.4 KiB
Quelques fois par année
624 
De une à trois fois par mois
356 
Une fois par semaine ou plus
240 
Moins d'une fois par année
134 
Jamais
94 

Length

Max length28
Median length26
Mean length24.232044
Min length6

Characters and Unicode

Total characters35088
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDe une à trois fois par mois
2nd rowUne fois par semaine ou plus
3rd rowUne fois par semaine ou plus
4th rowUne fois par semaine ou plus
5th rowQuelques fois par année

Common Values

ValueCountFrequency (%)
Quelques fois par année 624
43.1%
De une à trois fois par mois 356
24.6%
Une fois par semaine ou plus 240
 
16.6%
Moins d'une fois par année 134
 
9.3%
Jamais 94
 
6.5%

Length

2023-06-18T04:18:12.692167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:12.992127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
fois 1354
18.8%
par 1354
18.8%
année 758
10.5%
quelques 624
8.7%
une 596
8.3%
de 356
 
4.9%
à 356
 
4.9%
trois 356
 
4.9%
mois 356
 
4.9%
semaine 240
 
3.3%
Other values (5) 842
11.7%

Most occurring characters

ValueCountFrequency (%)
5744
16.4%
e 3572
10.2%
s 3398
9.7%
n 2620
 
7.5%
a 2540
 
7.2%
i 2534
 
7.2%
o 2440
 
7.0%
u 2218
 
6.3%
r 1710
 
4.9%
p 1594
 
4.5%
Other values (14) 6718
19.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27762
79.1%
Space Separator 5744
 
16.4%
Uppercase Letter 1448
 
4.1%
Other Punctuation 134
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3572
12.9%
s 3398
12.2%
n 2620
9.4%
a 2540
9.1%
i 2534
9.1%
o 2440
8.8%
u 2218
8.0%
r 1710
6.2%
p 1594
5.7%
f 1354
 
4.9%
Other values (7) 3782
13.6%
Uppercase Letter
ValueCountFrequency (%)
Q 624
43.1%
D 356
24.6%
U 240
 
16.6%
M 134
 
9.3%
J 94
 
6.5%
Space Separator
ValueCountFrequency (%)
5744
100.0%
Other Punctuation
ValueCountFrequency (%)
' 134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29210
83.2%
Common 5878
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3572
12.2%
s 3398
11.6%
n 2620
9.0%
a 2540
8.7%
i 2534
8.7%
o 2440
8.4%
u 2218
7.6%
r 1710
 
5.9%
p 1594
 
5.5%
f 1354
 
4.6%
Other values (12) 5230
17.9%
Common
ValueCountFrequency (%)
5744
97.7%
' 134
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33974
96.8%
None 1114
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5744
16.9%
e 3572
10.5%
s 3398
10.0%
n 2620
7.7%
a 2540
7.5%
i 2534
7.5%
o 2440
7.2%
u 2218
 
6.5%
r 1710
 
5.0%
p 1594
 
4.7%
Other values (12) 5604
16.5%
None
ValueCountFrequency (%)
é 758
68.0%
à 356
32.0%

acces_services _ Ville_q4
Categorical

Distinct4
Distinct (%)0.3%
Missing94
Missing (%)6.5%
Memory size159.9 KiB
Plutôt en accord
918 
Plutôt en désaccord
200 
Tout à fait en accord
184 
Tout à fait en désaccord
 
52

Length

Max length24
Median length16
Mean length17.429838
Min length16

Characters and Unicode

Total characters23600
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en accord
2nd rowPlutôt en accord
3rd rowPlutôt en accord
4th rowPlutôt en accord
5th rowPlutôt en accord

Common Values

ValueCountFrequency (%)
Plutôt en accord 918
63.4%
Plutôt en désaccord 200
 
13.8%
Tout à fait en accord 184
 
12.7%
Tout à fait en désaccord 52
 
3.6%
(Missing) 94
 
6.5%

Length

2023-06-18T04:18:13.260185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:13.537587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1354
29.9%
plutôt 1118
24.7%
accord 1102
24.3%
désaccord 252
 
5.6%
tout 236
 
5.2%
à 236
 
5.2%
fait 236
 
5.2%

Most occurring characters

ValueCountFrequency (%)
3180
13.5%
c 2708
11.5%
t 2708
11.5%
d 1606
 
6.8%
o 1590
 
6.7%
a 1590
 
6.7%
u 1354
 
5.7%
e 1354
 
5.7%
n 1354
 
5.7%
r 1354
 
5.7%
Other values (9) 4802
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19066
80.8%
Space Separator 3180
 
13.5%
Uppercase Letter 1354
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2708
14.2%
t 2708
14.2%
d 1606
8.4%
o 1590
8.3%
a 1590
8.3%
u 1354
7.1%
e 1354
7.1%
n 1354
7.1%
r 1354
7.1%
l 1118
5.9%
Other values (6) 2330
12.2%
Uppercase Letter
ValueCountFrequency (%)
P 1118
82.6%
T 236
 
17.4%
Space Separator
ValueCountFrequency (%)
3180
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20420
86.5%
Common 3180
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2708
13.3%
t 2708
13.3%
d 1606
7.9%
o 1590
7.8%
a 1590
7.8%
u 1354
 
6.6%
e 1354
 
6.6%
n 1354
 
6.6%
r 1354
 
6.6%
P 1118
 
5.5%
Other values (8) 3684
18.0%
Common
ValueCountFrequency (%)
3180
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21994
93.2%
None 1606
 
6.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3180
14.5%
c 2708
12.3%
t 2708
12.3%
d 1606
7.3%
o 1590
7.2%
a 1590
7.2%
u 1354
6.2%
e 1354
6.2%
n 1354
6.2%
r 1354
6.2%
Other values (6) 3196
14.5%
None
ValueCountFrequency (%)
ô 1118
69.6%
é 252
 
15.7%
à 236
 
14.7%

acces_services _ Ville_q5
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size176.8 KiB
Tout à fait en désaccord
562 
Plutôt en désaccord
536 
Plutôt en accord
244 
Tout à fait en accord
106 

Length

Max length24
Median length21
Mean length20.581492
Min length16

Characters and Unicode

Total characters29802
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en accord
2nd rowPlutôt en désaccord
3rd rowPlutôt en désaccord
4th rowPlutôt en accord
5th rowPlutôt en désaccord

Common Values

ValueCountFrequency (%)
Tout à fait en désaccord 562
38.8%
Plutôt en désaccord 536
37.0%
Plutôt en accord 244
16.9%
Tout à fait en accord 106
 
7.3%

Length

2023-06-18T04:18:13.800866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:14.087084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1448
25.5%
désaccord 1098
19.3%
plutôt 780
13.7%
tout 668
11.8%
à 668
11.8%
fait 668
11.8%
accord 350
 
6.2%

Most occurring characters

ValueCountFrequency (%)
4232
14.2%
c 2896
9.7%
t 2896
9.7%
d 2546
 
8.5%
a 2116
 
7.1%
o 2116
 
7.1%
e 1448
 
4.9%
u 1448
 
4.9%
r 1448
 
4.9%
n 1448
 
4.9%
Other values (9) 7208
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24122
80.9%
Space Separator 4232
 
14.2%
Uppercase Letter 1448
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2896
12.0%
t 2896
12.0%
d 2546
10.6%
a 2116
8.8%
o 2116
8.8%
e 1448
 
6.0%
u 1448
 
6.0%
r 1448
 
6.0%
n 1448
 
6.0%
é 1098
 
4.6%
Other values (6) 4662
19.3%
Uppercase Letter
ValueCountFrequency (%)
P 780
53.9%
T 668
46.1%
Space Separator
ValueCountFrequency (%)
4232
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25570
85.8%
Common 4232
 
14.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2896
11.3%
t 2896
11.3%
d 2546
10.0%
a 2116
 
8.3%
o 2116
 
8.3%
e 1448
 
5.7%
u 1448
 
5.7%
r 1448
 
5.7%
n 1448
 
5.7%
é 1098
 
4.3%
Other values (8) 6110
23.9%
Common
ValueCountFrequency (%)
4232
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27256
91.5%
None 2546
 
8.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4232
15.5%
c 2896
10.6%
t 2896
10.6%
d 2546
9.3%
a 2116
7.8%
o 2116
7.8%
e 1448
 
5.3%
u 1448
 
5.3%
r 1448
 
5.3%
n 1448
 
5.3%
Other values (6) 4662
17.1%
None
ValueCountFrequency (%)
é 1098
43.1%
ô 780
30.6%
à 668
26.2%

acces_services _ Ville_q6_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing1342
Missing (%)92.7%
Memory size66.3 KiB
Bibliothèques municipales
106 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2650
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBibliothèques municipales
2nd rowBibliothèques municipales
3rd rowBibliothèques municipales
4th rowBibliothèques municipales
5th rowBibliothèques municipales

Common Values

ValueCountFrequency (%)
Bibliothèques municipales 106
 
7.3%
(Missing) 1342
92.7%

Length

2023-06-18T04:18:14.321929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:14.541297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
bibliothèques 106
50.0%
municipales 106
50.0%

Most occurring characters

ValueCountFrequency (%)
i 424
16.0%
u 212
 
8.0%
e 212
 
8.0%
l 212
 
8.0%
s 212
 
8.0%
p 106
 
4.0%
c 106
 
4.0%
n 106
 
4.0%
m 106
 
4.0%
106
 
4.0%
Other values (8) 848
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2438
92.0%
Space Separator 106
 
4.0%
Uppercase Letter 106
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 424
17.4%
u 212
 
8.7%
e 212
 
8.7%
l 212
 
8.7%
s 212
 
8.7%
p 106
 
4.3%
c 106
 
4.3%
n 106
 
4.3%
m 106
 
4.3%
q 106
 
4.3%
Other values (6) 636
26.1%
Space Separator
ValueCountFrequency (%)
106
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2544
96.0%
Common 106
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 424
16.7%
u 212
 
8.3%
e 212
 
8.3%
l 212
 
8.3%
s 212
 
8.3%
p 106
 
4.2%
c 106
 
4.2%
n 106
 
4.2%
m 106
 
4.2%
B 106
 
4.2%
Other values (7) 742
29.2%
Common
ValueCountFrequency (%)
106
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2544
96.0%
None 106
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 424
16.7%
u 212
 
8.3%
e 212
 
8.3%
l 212
 
8.3%
s 212
 
8.3%
p 106
 
4.2%
c 106
 
4.2%
n 106
 
4.2%
m 106
 
4.2%
106
 
4.2%
Other values (7) 742
29.2%
None
ValueCountFrequency (%)
è 106
100.0%

acces_services _ Ville_q6_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing1321
Missing (%)91.2%
Memory size67.6 KiB
Bureaux Accès Montréal
127 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters2794
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBureaux Accès Montréal
2nd rowBureaux Accès Montréal
3rd rowBureaux Accès Montréal
4th rowBureaux Accès Montréal
5th rowBureaux Accès Montréal

Common Values

ValueCountFrequency (%)
Bureaux Accès Montréal 127
 
8.8%
(Missing) 1321
91.2%

Length

2023-06-18T04:18:14.731590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:14.983129image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
bureaux 127
33.3%
accès 127
33.3%
montréal 127
33.3%

Most occurring characters

ValueCountFrequency (%)
c 254
 
9.1%
r 254
 
9.1%
a 254
 
9.1%
254
 
9.1%
u 254
 
9.1%
M 127
 
4.5%
é 127
 
4.5%
t 127
 
4.5%
n 127
 
4.5%
o 127
 
4.5%
Other values (7) 889
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2159
77.3%
Uppercase Letter 381
 
13.6%
Space Separator 254
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 254
11.8%
r 254
11.8%
a 254
11.8%
u 254
11.8%
é 127
 
5.9%
t 127
 
5.9%
n 127
 
5.9%
o 127
 
5.9%
s 127
 
5.9%
è 127
 
5.9%
Other values (3) 381
17.6%
Uppercase Letter
ValueCountFrequency (%)
M 127
33.3%
B 127
33.3%
A 127
33.3%
Space Separator
ValueCountFrequency (%)
254
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2540
90.9%
Common 254
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 254
 
10.0%
r 254
 
10.0%
a 254
 
10.0%
u 254
 
10.0%
M 127
 
5.0%
é 127
 
5.0%
t 127
 
5.0%
n 127
 
5.0%
o 127
 
5.0%
B 127
 
5.0%
Other values (6) 762
30.0%
Common
ValueCountFrequency (%)
254
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2540
90.9%
None 254
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 254
 
10.0%
r 254
 
10.0%
a 254
 
10.0%
254
 
10.0%
u 254
 
10.0%
M 127
 
5.0%
t 127
 
5.0%
n 127
 
5.0%
o 127
 
5.0%
B 127
 
5.0%
Other values (5) 635
25.0%
None
ValueCountFrequency (%)
é 127
50.0%
è 127
50.0%

acces_services _ Ville_q6_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.1%
Missing1356
Missing (%)93.6%
Memory size68.7 KiB
Réseau Accès culture ou Maisons de la culture
92 

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters4140
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRéseau Accès culture ou Maisons de la culture
2nd rowRéseau Accès culture ou Maisons de la culture
3rd rowRéseau Accès culture ou Maisons de la culture
4th rowRéseau Accès culture ou Maisons de la culture
5th rowRéseau Accès culture ou Maisons de la culture

Common Values

ValueCountFrequency (%)
Réseau Accès culture ou Maisons de la culture 92
 
6.4%
(Missing) 1356
93.6%

Length

2023-06-18T04:18:15.166388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:15.378730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
culture 184
25.0%
réseau 92
12.5%
accès 92
12.5%
ou 92
12.5%
maisons 92
12.5%
de 92
12.5%
la 92
12.5%

Most occurring characters

ValueCountFrequency (%)
644
15.6%
u 552
13.3%
s 368
8.9%
e 368
8.9%
c 368
8.9%
a 276
 
6.7%
l 276
 
6.7%
t 184
 
4.4%
r 184
 
4.4%
o 184
 
4.4%
Other values (8) 736
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3220
77.8%
Space Separator 644
 
15.6%
Uppercase Letter 276
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 552
17.1%
s 368
11.4%
e 368
11.4%
c 368
11.4%
a 276
8.6%
l 276
8.6%
t 184
 
5.7%
r 184
 
5.7%
o 184
 
5.7%
n 92
 
2.9%
Other values (4) 368
11.4%
Uppercase Letter
ValueCountFrequency (%)
R 92
33.3%
M 92
33.3%
A 92
33.3%
Space Separator
ValueCountFrequency (%)
644
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3496
84.4%
Common 644
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 552
15.8%
s 368
10.5%
e 368
10.5%
c 368
10.5%
a 276
7.9%
l 276
7.9%
t 184
 
5.3%
r 184
 
5.3%
o 184
 
5.3%
R 92
 
2.6%
Other values (7) 644
18.4%
Common
ValueCountFrequency (%)
644
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3956
95.6%
None 184
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
644
16.3%
u 552
14.0%
s 368
9.3%
e 368
9.3%
c 368
9.3%
a 276
7.0%
l 276
7.0%
t 184
 
4.7%
r 184
 
4.7%
o 184
 
4.7%
Other values (6) 552
14.0%
None
ValueCountFrequency (%)
è 92
50.0%
é 92
50.0%

acces_services _ Ville_q6_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1194
Missing (%)82.5%
Memory size77.3 KiB
Centres sportifs et de loisirs (piscine, terrains de tennis, etc.)
254 

Length

Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

Total characters16764
Distinct characters19
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)
2nd rowCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)
3rd rowCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)
4th rowCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)
5th rowCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)

Common Values

ValueCountFrequency (%)
Centres sportifs et de loisirs (piscine, terrains de tennis, etc.) 254
 
17.5%
(Missing) 1194
82.5%

Length

2023-06-18T04:18:15.561846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:15.788073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 508
20.0%
centres 254
10.0%
sportifs 254
10.0%
et 254
10.0%
loisirs 254
10.0%
piscine 254
10.0%
terrains 254
10.0%
tennis 254
10.0%
etc 254
10.0%

Most occurring characters

ValueCountFrequency (%)
2286
13.6%
e 2286
13.6%
s 2032
12.1%
i 1778
10.6%
t 1524
9.1%
n 1270
7.6%
r 1270
7.6%
c 508
 
3.0%
p 508
 
3.0%
o 508
 
3.0%
Other values (9) 2794
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12954
77.3%
Space Separator 2286
 
13.6%
Other Punctuation 762
 
4.5%
Uppercase Letter 254
 
1.5%
Open Punctuation 254
 
1.5%
Close Punctuation 254
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2286
17.6%
s 2032
15.7%
i 1778
13.7%
t 1524
11.8%
n 1270
9.8%
r 1270
9.8%
c 508
 
3.9%
p 508
 
3.9%
o 508
 
3.9%
d 508
 
3.9%
Other values (3) 762
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 508
66.7%
. 254
33.3%
Space Separator
ValueCountFrequency (%)
2286
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 254
100.0%
Open Punctuation
ValueCountFrequency (%)
( 254
100.0%
Close Punctuation
ValueCountFrequency (%)
) 254
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13208
78.8%
Common 3556
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2286
17.3%
s 2032
15.4%
i 1778
13.5%
t 1524
11.5%
n 1270
9.6%
r 1270
9.6%
c 508
 
3.8%
p 508
 
3.8%
o 508
 
3.8%
d 508
 
3.8%
Other values (4) 1016
7.7%
Common
ValueCountFrequency (%)
2286
64.3%
, 508
 
14.3%
. 254
 
7.1%
( 254
 
7.1%
) 254
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16764
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2286
13.6%
e 2286
13.6%
s 2032
12.1%
i 1778
10.6%
t 1524
9.1%
n 1270
7.6%
r 1270
7.6%
c 508
 
3.0%
p 508
 
3.0%
o 508
 
3.0%
Other values (9) 2794
16.7%

acces_services _ Ville_q6_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing1281
Missing (%)88.5%
Memory size78.1 KiB
Réseau des parcs de quartier et grands parcs
167 

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters7348
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRéseau des parcs de quartier et grands parcs
2nd rowRéseau des parcs de quartier et grands parcs
3rd rowRéseau des parcs de quartier et grands parcs
4th rowRéseau des parcs de quartier et grands parcs
5th rowRéseau des parcs de quartier et grands parcs

Common Values

ValueCountFrequency (%)
Réseau des parcs de quartier et grands parcs 167
 
11.5%
(Missing) 1281
88.5%

Length

2023-06-18T04:18:15.989375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:16.218103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
parcs 334
25.0%
réseau 167
12.5%
des 167
12.5%
de 167
12.5%
quartier 167
12.5%
et 167
12.5%
grands 167
12.5%

Most occurring characters

ValueCountFrequency (%)
1169
15.9%
s 835
11.4%
e 835
11.4%
a 835
11.4%
r 835
11.4%
d 501
6.8%
u 334
 
4.5%
p 334
 
4.5%
c 334
 
4.5%
t 334
 
4.5%
Other values (6) 1002
13.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6012
81.8%
Space Separator 1169
 
15.9%
Uppercase Letter 167
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 835
13.9%
e 835
13.9%
a 835
13.9%
r 835
13.9%
d 501
8.3%
u 334
 
5.6%
p 334
 
5.6%
c 334
 
5.6%
t 334
 
5.6%
é 167
 
2.8%
Other values (4) 668
11.1%
Space Separator
ValueCountFrequency (%)
1169
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 167
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6179
84.1%
Common 1169
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 835
13.5%
e 835
13.5%
a 835
13.5%
r 835
13.5%
d 501
8.1%
u 334
 
5.4%
p 334
 
5.4%
c 334
 
5.4%
t 334
 
5.4%
R 167
 
2.7%
Other values (5) 835
13.5%
Common
ValueCountFrequency (%)
1169
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7181
97.7%
None 167
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1169
16.3%
s 835
11.6%
e 835
11.6%
a 835
11.6%
r 835
11.6%
d 501
7.0%
u 334
 
4.7%
p 334
 
4.7%
c 334
 
4.7%
t 334
 
4.7%
Other values (5) 835
11.6%
None
ValueCountFrequency (%)
é 167
100.0%

acces_services _ Ville_q6_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.4%
Missing1376
Missing (%)95.0%
Memory size59.4 KiB
Jardins communautaires
72 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1584
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJardins communautaires
2nd rowJardins communautaires
3rd rowJardins communautaires
4th rowJardins communautaires
5th rowJardins communautaires

Common Values

ValueCountFrequency (%)
Jardins communautaires 72
 
5.0%
(Missing) 1376
95.0%

Length

2023-06-18T04:18:16.417000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:16.655428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
jardins 72
50.0%
communautaires 72
50.0%

Most occurring characters

ValueCountFrequency (%)
a 216
13.6%
r 144
9.1%
i 144
9.1%
n 144
9.1%
s 144
9.1%
m 144
9.1%
u 144
9.1%
J 72
 
4.5%
d 72
 
4.5%
72
 
4.5%
Other values (4) 288
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1440
90.9%
Uppercase Letter 72
 
4.5%
Space Separator 72
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 216
15.0%
r 144
10.0%
i 144
10.0%
n 144
10.0%
s 144
10.0%
m 144
10.0%
u 144
10.0%
d 72
 
5.0%
c 72
 
5.0%
o 72
 
5.0%
Other values (2) 144
10.0%
Uppercase Letter
ValueCountFrequency (%)
J 72
100.0%
Space Separator
ValueCountFrequency (%)
72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1512
95.5%
Common 72
 
4.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 216
14.3%
r 144
9.5%
i 144
9.5%
n 144
9.5%
s 144
9.5%
m 144
9.5%
u 144
9.5%
J 72
 
4.8%
d 72
 
4.8%
c 72
 
4.8%
Other values (3) 216
14.3%
Common
ValueCountFrequency (%)
72
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 216
13.6%
r 144
9.1%
i 144
9.1%
n 144
9.1%
s 144
9.1%
m 144
9.1%
u 144
9.1%
J 72
 
4.5%
d 72
 
4.5%
72
 
4.5%
Other values (4) 288
18.2%

acces_services _ Ville_q6_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.8%
Missing1392
Missing (%)96.1%
Memory size61.5 KiB
Ligne téléphonique 311
56 

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters1232
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLigne téléphonique 311
2nd rowLigne téléphonique 311
3rd rowLigne téléphonique 311
4th rowLigne téléphonique 311
5th rowLigne téléphonique 311

Common Values

ValueCountFrequency (%)
Ligne téléphonique 311 56
 
3.9%
(Missing) 1392
96.1%

Length

2023-06-18T04:18:16.854641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:17.088268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ligne 56
33.3%
téléphonique 56
33.3%
311 56
33.3%

Most occurring characters

ValueCountFrequency (%)
i 112
 
9.1%
n 112
 
9.1%
e 112
 
9.1%
112
 
9.1%
é 112
 
9.1%
1 112
 
9.1%
L 56
 
4.5%
g 56
 
4.5%
t 56
 
4.5%
l 56
 
4.5%
Other values (6) 336
27.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 896
72.7%
Decimal Number 168
 
13.6%
Space Separator 112
 
9.1%
Uppercase Letter 56
 
4.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 112
12.5%
n 112
12.5%
e 112
12.5%
é 112
12.5%
g 56
6.2%
t 56
6.2%
l 56
6.2%
p 56
6.2%
h 56
6.2%
o 56
6.2%
Other values (2) 112
12.5%
Decimal Number
ValueCountFrequency (%)
1 112
66.7%
3 56
33.3%
Space Separator
ValueCountFrequency (%)
112
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 952
77.3%
Common 280
 
22.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 112
11.8%
n 112
11.8%
e 112
11.8%
é 112
11.8%
L 56
 
5.9%
g 56
 
5.9%
t 56
 
5.9%
l 56
 
5.9%
p 56
 
5.9%
h 56
 
5.9%
Other values (3) 168
17.6%
Common
ValueCountFrequency (%)
112
40.0%
1 112
40.0%
3 56
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1120
90.9%
None 112
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 112
 
10.0%
n 112
 
10.0%
e 112
 
10.0%
112
 
10.0%
1 112
 
10.0%
L 56
 
5.0%
g 56
 
5.0%
t 56
 
5.0%
l 56
 
5.0%
p 56
 
5.0%
Other values (5) 280
25.0%
None
ValueCountFrequency (%)
é 112
100.0%

acces_services _ Ville_q7_1
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size90.3 KiB
Oui
574 
Je ne sais pas
495 
Non
379 

Length

Max length14
Median length3
Mean length6.7603591
Min length3

Characters and Unicode

Total characters9789
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui
2nd rowNon
3rd rowJe ne sais pas
4th rowJe ne sais pas
5th rowOui

Common Values

ValueCountFrequency (%)
Oui 574
39.6%
Je ne sais pas 495
34.2%
Non 379
26.2%

Length

2023-06-18T04:18:17.274200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:17.523821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 574
19.6%
je 495
16.9%
ne 495
16.9%
sais 495
16.9%
pas 495
16.9%
non 379
12.9%

Most occurring characters

ValueCountFrequency (%)
1485
15.2%
s 1485
15.2%
i 1069
10.9%
e 990
10.1%
a 990
10.1%
n 874
8.9%
O 574
 
5.9%
u 574
 
5.9%
J 495
 
5.1%
p 495
 
5.1%
Other values (2) 758
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6856
70.0%
Space Separator 1485
 
15.2%
Uppercase Letter 1448
 
14.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1485
21.7%
i 1069
15.6%
e 990
14.4%
a 990
14.4%
n 874
12.7%
u 574
 
8.4%
p 495
 
7.2%
o 379
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
O 574
39.6%
J 495
34.2%
N 379
26.2%
Space Separator
ValueCountFrequency (%)
1485
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8304
84.8%
Common 1485
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1485
17.9%
i 1069
12.9%
e 990
11.9%
a 990
11.9%
n 874
10.5%
O 574
 
6.9%
u 574
 
6.9%
J 495
 
6.0%
p 495
 
6.0%
N 379
 
4.6%
Common
ValueCountFrequency (%)
1485
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9789
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1485
15.2%
s 1485
15.2%
i 1069
10.9%
e 990
10.1%
a 990
10.1%
n 874
8.9%
O 574
 
5.9%
u 574
 
5.9%
J 495
 
5.1%
p 495
 
5.1%
Other values (2) 758
7.7%

acces_services _ Ville_q7_2
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.2 KiB
Oui
908 
Non
332 
Je ne sais pas
208 

Length

Max length14
Median length3
Mean length4.5801105
Min length3

Characters and Unicode

Total characters6632
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowOui
3rd rowOui
4th rowNon
5th rowOui

Common Values

ValueCountFrequency (%)
Oui 908
62.7%
Non 332
 
22.9%
Je ne sais pas 208
 
14.4%

Length

2023-06-18T04:18:17.753707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:18.049513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 908
43.8%
non 332
 
16.0%
je 208
 
10.0%
ne 208
 
10.0%
sais 208
 
10.0%
pas 208
 
10.0%

Most occurring characters

ValueCountFrequency (%)
i 1116
16.8%
O 908
13.7%
u 908
13.7%
624
9.4%
s 624
9.4%
n 540
8.1%
e 416
 
6.3%
a 416
 
6.3%
N 332
 
5.0%
o 332
 
5.0%
Other values (2) 416
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4560
68.8%
Uppercase Letter 1448
 
21.8%
Space Separator 624
 
9.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1116
24.5%
u 908
19.9%
s 624
13.7%
n 540
11.8%
e 416
 
9.1%
a 416
 
9.1%
o 332
 
7.3%
p 208
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
O 908
62.7%
N 332
 
22.9%
J 208
 
14.4%
Space Separator
ValueCountFrequency (%)
624
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6008
90.6%
Common 624
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1116
18.6%
O 908
15.1%
u 908
15.1%
s 624
10.4%
n 540
9.0%
e 416
 
6.9%
a 416
 
6.9%
N 332
 
5.5%
o 332
 
5.5%
J 208
 
3.5%
Common
ValueCountFrequency (%)
624
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1116
16.8%
O 908
13.7%
u 908
13.7%
624
9.4%
s 624
9.4%
n 540
8.1%
e 416
 
6.3%
a 416
 
6.3%
N 332
 
5.0%
o 332
 
5.0%
Other values (2) 416
 
6.3%

acces_services _ Ville_q7_3
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.4 KiB
Oui
872 
Non
348 
Je ne sais pas
228 

Length

Max length14
Median length3
Mean length4.7320442
Min length3

Characters and Unicode

Total characters6852
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowOui
3rd rowOui
4th rowNon
5th rowOui

Common Values

ValueCountFrequency (%)
Oui 872
60.2%
Non 348
 
24.0%
Je ne sais pas 228
 
15.7%

Length

2023-06-18T04:18:18.353471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:18.823777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 872
40.9%
non 348
 
16.3%
je 228
 
10.7%
ne 228
 
10.7%
sais 228
 
10.7%
pas 228
 
10.7%

Most occurring characters

ValueCountFrequency (%)
i 1100
16.1%
O 872
12.7%
u 872
12.7%
684
10.0%
s 684
10.0%
n 576
8.4%
e 456
6.7%
a 456
6.7%
N 348
 
5.1%
o 348
 
5.1%
Other values (2) 456
6.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4720
68.9%
Uppercase Letter 1448
 
21.1%
Space Separator 684
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1100
23.3%
u 872
18.5%
s 684
14.5%
n 576
12.2%
e 456
9.7%
a 456
9.7%
o 348
 
7.4%
p 228
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
O 872
60.2%
N 348
 
24.0%
J 228
 
15.7%
Space Separator
ValueCountFrequency (%)
684
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6168
90.0%
Common 684
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1100
17.8%
O 872
14.1%
u 872
14.1%
s 684
11.1%
n 576
9.3%
e 456
7.4%
a 456
7.4%
N 348
 
5.6%
o 348
 
5.6%
J 228
 
3.7%
Common
ValueCountFrequency (%)
684
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1100
16.1%
O 872
12.7%
u 872
12.7%
684
10.0%
s 684
10.0%
n 576
8.4%
e 456
6.7%
a 456
6.7%
N 348
 
5.1%
o 348
 
5.1%
Other values (2) 456
6.7%

acces_services _ Ville_q7_4
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size86.7 KiB
Oui
732 
Non
554 
Je ne sais pas
162 

Length

Max length14
Median length3
Mean length4.230663
Min length3

Characters and Unicode

Total characters6126
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowOui
3rd rowNon
4th rowOui
5th rowNon

Common Values

ValueCountFrequency (%)
Oui 732
50.6%
Non 554
38.3%
Je ne sais pas 162
 
11.2%

Length

2023-06-18T04:18:19.255610image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:19.721543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 732
37.8%
non 554
28.6%
je 162
 
8.4%
ne 162
 
8.4%
sais 162
 
8.4%
pas 162
 
8.4%

Most occurring characters

ValueCountFrequency (%)
i 894
14.6%
O 732
11.9%
u 732
11.9%
n 716
11.7%
N 554
9.0%
o 554
9.0%
486
7.9%
s 486
7.9%
e 324
 
5.3%
a 324
 
5.3%
Other values (2) 324
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4192
68.4%
Uppercase Letter 1448
 
23.6%
Space Separator 486
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 894
21.3%
u 732
17.5%
n 716
17.1%
o 554
13.2%
s 486
11.6%
e 324
 
7.7%
a 324
 
7.7%
p 162
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
O 732
50.6%
N 554
38.3%
J 162
 
11.2%
Space Separator
ValueCountFrequency (%)
486
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5640
92.1%
Common 486
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 894
15.9%
O 732
13.0%
u 732
13.0%
n 716
12.7%
N 554
9.8%
o 554
9.8%
s 486
8.6%
e 324
 
5.7%
a 324
 
5.7%
J 162
 
2.9%
Common
ValueCountFrequency (%)
486
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 894
14.6%
O 732
11.9%
u 732
11.9%
n 716
11.7%
N 554
9.0%
o 554
9.0%
486
7.9%
s 486
7.9%
e 324
 
5.3%
a 324
 
5.3%
Other values (2) 324
 
5.3%

acces_services _ Ville_q7_5
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size89.0 KiB
Oui
716 
Je ne sais pas
379 
Non
353 

Length

Max length14
Median length3
Mean length5.8791436
Min length3

Characters and Unicode

Total characters8513
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowOui
4th rowNon
5th rowOui

Common Values

ValueCountFrequency (%)
Oui 716
49.4%
Je ne sais pas 379
26.2%
Non 353
24.4%

Length

2023-06-18T04:18:20.086387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:20.498471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 716
27.7%
je 379
14.7%
ne 379
14.7%
sais 379
14.7%
pas 379
14.7%
non 353
13.7%

Most occurring characters

ValueCountFrequency (%)
1137
13.4%
s 1137
13.4%
i 1095
12.9%
e 758
8.9%
a 758
8.9%
n 732
8.6%
O 716
8.4%
u 716
8.4%
J 379
 
4.5%
p 379
 
4.5%
Other values (2) 706
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5928
69.6%
Uppercase Letter 1448
 
17.0%
Space Separator 1137
 
13.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1137
19.2%
i 1095
18.5%
e 758
12.8%
a 758
12.8%
n 732
12.3%
u 716
12.1%
p 379
 
6.4%
o 353
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
O 716
49.4%
J 379
26.2%
N 353
24.4%
Space Separator
ValueCountFrequency (%)
1137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7376
86.6%
Common 1137
 
13.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1137
15.4%
i 1095
14.8%
e 758
10.3%
a 758
10.3%
n 732
9.9%
O 716
9.7%
u 716
9.7%
J 379
 
5.1%
p 379
 
5.1%
N 353
 
4.8%
Common
ValueCountFrequency (%)
1137
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1137
13.4%
s 1137
13.4%
i 1095
12.9%
e 758
8.9%
a 758
8.9%
n 732
8.6%
O 716
8.4%
u 716
8.4%
J 379
 
4.5%
p 379
 
4.5%
Other values (2) 706
8.3%

acces_services _ Ville_q8_1
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size89.8 KiB
Non
834 
Je ne sais pas
446 
Oui
168 

Length

Max length14
Median length3
Mean length6.3881215
Min length3

Characters and Unicode

Total characters9250
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowOui
3rd rowNon
4th rowJe ne sais pas
5th rowNon

Common Values

ValueCountFrequency (%)
Non 834
57.6%
Je ne sais pas 446
30.8%
Oui 168
 
11.6%

Length

2023-06-18T04:18:20.944491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:21.453012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 834
29.9%
je 446
16.0%
ne 446
16.0%
sais 446
16.0%
pas 446
16.0%
oui 168
 
6.0%

Most occurring characters

ValueCountFrequency (%)
1338
14.5%
s 1338
14.5%
n 1280
13.8%
e 892
9.6%
a 892
9.6%
N 834
9.0%
o 834
9.0%
i 614
6.6%
J 446
 
4.8%
p 446
 
4.8%
Other values (2) 336
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6464
69.9%
Uppercase Letter 1448
 
15.7%
Space Separator 1338
 
14.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1338
20.7%
n 1280
19.8%
e 892
13.8%
a 892
13.8%
o 834
12.9%
i 614
9.5%
p 446
 
6.9%
u 168
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
N 834
57.6%
J 446
30.8%
O 168
 
11.6%
Space Separator
ValueCountFrequency (%)
1338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7912
85.5%
Common 1338
 
14.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1338
16.9%
n 1280
16.2%
e 892
11.3%
a 892
11.3%
N 834
10.5%
o 834
10.5%
i 614
7.8%
J 446
 
5.6%
p 446
 
5.6%
O 168
 
2.1%
Common
ValueCountFrequency (%)
1338
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9250
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1338
14.5%
s 1338
14.5%
n 1280
13.8%
e 892
9.6%
a 892
9.6%
N 834
9.0%
o 834
9.0%
i 614
6.6%
J 446
 
4.8%
p 446
 
4.8%
Other values (2) 336
 
3.6%

acces_services _ Ville_q8_2
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.0 KiB
Non
898 
Oui
362 
Je ne sais pas
188 

Length

Max length14
Median length3
Mean length4.4281768
Min length3

Characters and Unicode

Total characters6412
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe ne sais pas
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 898
62.0%
Oui 362
25.0%
Je ne sais pas 188
 
13.0%

Length

2023-06-18T04:18:21.689610image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:21.951375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 898
44.6%
oui 362
18.0%
je 188
 
9.3%
ne 188
 
9.3%
sais 188
 
9.3%
pas 188
 
9.3%

Most occurring characters

ValueCountFrequency (%)
n 1086
16.9%
N 898
14.0%
o 898
14.0%
564
8.8%
s 564
8.8%
i 550
8.6%
e 376
 
5.9%
a 376
 
5.9%
O 362
 
5.6%
u 362
 
5.6%
Other values (2) 376
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4400
68.6%
Uppercase Letter 1448
 
22.6%
Space Separator 564
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1086
24.7%
o 898
20.4%
s 564
12.8%
i 550
12.5%
e 376
 
8.5%
a 376
 
8.5%
u 362
 
8.2%
p 188
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
N 898
62.0%
O 362
25.0%
J 188
 
13.0%
Space Separator
ValueCountFrequency (%)
564
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5848
91.2%
Common 564
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1086
18.6%
N 898
15.4%
o 898
15.4%
s 564
9.6%
i 550
9.4%
e 376
 
6.4%
a 376
 
6.4%
O 362
 
6.2%
u 362
 
6.2%
J 188
 
3.2%
Common
ValueCountFrequency (%)
564
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1086
16.9%
N 898
14.0%
o 898
14.0%
564
8.8%
s 564
8.8%
i 550
8.6%
e 376
 
5.9%
a 376
 
5.9%
O 362
 
5.6%
u 362
 
5.6%
Other values (2) 376
 
5.9%

acces_services _ Ville_q8_3
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.2 KiB
Non
969 
Oui
271 
Je ne sais pas
208 

Length

Max length14
Median length3
Mean length4.5801105
Min length3

Characters and Unicode

Total characters6632
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe ne sais pas
2nd rowOui
3rd rowNon
4th rowJe ne sais pas
5th rowNon

Common Values

ValueCountFrequency (%)
Non 969
66.9%
Oui 271
 
18.7%
Je ne sais pas 208
 
14.4%

Length

2023-06-18T04:18:22.194876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:22.933665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 969
46.8%
oui 271
 
13.1%
je 208
 
10.0%
ne 208
 
10.0%
sais 208
 
10.0%
pas 208
 
10.0%

Most occurring characters

ValueCountFrequency (%)
n 1177
17.7%
N 969
14.6%
o 969
14.6%
624
9.4%
s 624
9.4%
i 479
7.2%
e 416
 
6.3%
a 416
 
6.3%
O 271
 
4.1%
u 271
 
4.1%
Other values (2) 416
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4560
68.8%
Uppercase Letter 1448
 
21.8%
Space Separator 624
 
9.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1177
25.8%
o 969
21.2%
s 624
13.7%
i 479
10.5%
e 416
 
9.1%
a 416
 
9.1%
u 271
 
5.9%
p 208
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
N 969
66.9%
O 271
 
18.7%
J 208
 
14.4%
Space Separator
ValueCountFrequency (%)
624
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6008
90.6%
Common 624
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1177
19.6%
N 969
16.1%
o 969
16.1%
s 624
10.4%
i 479
8.0%
e 416
 
6.9%
a 416
 
6.9%
O 271
 
4.5%
u 271
 
4.5%
J 208
 
3.5%
Common
ValueCountFrequency (%)
624
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1177
17.7%
N 969
14.6%
o 969
14.6%
624
9.4%
s 624
9.4%
i 479
7.2%
e 416
 
6.3%
a 416
 
6.3%
O 271
 
4.1%
u 271
 
4.1%
Other values (2) 416
 
6.3%

acces_services _ Ville_q8_4
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size87.0 KiB
Non
864 
Oui
394 
Je ne sais pas
190 

Length

Max length14
Median length3
Mean length4.4433702
Min length3

Characters and Unicode

Total characters6434
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 864
59.7%
Oui 394
27.2%
Je ne sais pas 190
 
13.1%

Length

2023-06-18T04:18:23.190861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:23.446819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 864
42.8%
oui 394
19.5%
je 190
 
9.4%
ne 190
 
9.4%
sais 190
 
9.4%
pas 190
 
9.4%

Most occurring characters

ValueCountFrequency (%)
n 1054
16.4%
N 864
13.4%
o 864
13.4%
i 584
9.1%
570
8.9%
s 570
8.9%
O 394
 
6.1%
u 394
 
6.1%
e 380
 
5.9%
a 380
 
5.9%
Other values (2) 380
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4416
68.6%
Uppercase Letter 1448
 
22.5%
Space Separator 570
 
8.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1054
23.9%
o 864
19.6%
i 584
13.2%
s 570
12.9%
u 394
 
8.9%
e 380
 
8.6%
a 380
 
8.6%
p 190
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
N 864
59.7%
O 394
27.2%
J 190
 
13.1%
Space Separator
ValueCountFrequency (%)
570
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5864
91.1%
Common 570
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1054
18.0%
N 864
14.7%
o 864
14.7%
i 584
10.0%
s 570
9.7%
O 394
 
6.7%
u 394
 
6.7%
e 380
 
6.5%
a 380
 
6.5%
J 190
 
3.2%
Common
ValueCountFrequency (%)
570
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6434
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1054
16.4%
N 864
13.4%
o 864
13.4%
i 584
9.1%
570
8.9%
s 570
8.9%
O 394
 
6.1%
u 394
 
6.1%
e 380
 
5.9%
a 380
 
5.9%
Other values (2) 380
 
5.9%

acces_services _ Ville_q8_5
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size89.0 KiB
Non
757 
Je ne sais pas
371 
Oui
320 

Length

Max length14
Median length3
Mean length5.8183702
Min length3

Characters and Unicode

Total characters8425
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui
2nd rowOui
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 757
52.3%
Je ne sais pas 371
25.6%
Oui 320
22.1%

Length

2023-06-18T04:18:23.660512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:23.926650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 757
29.6%
je 371
14.5%
ne 371
14.5%
sais 371
14.5%
pas 371
14.5%
oui 320
12.5%

Most occurring characters

ValueCountFrequency (%)
n 1128
13.4%
1113
13.2%
s 1113
13.2%
N 757
9.0%
o 757
9.0%
e 742
8.8%
a 742
8.8%
i 691
8.2%
J 371
 
4.4%
p 371
 
4.4%
Other values (2) 640
7.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5864
69.6%
Uppercase Letter 1448
 
17.2%
Space Separator 1113
 
13.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1128
19.2%
s 1113
19.0%
o 757
12.9%
e 742
12.7%
a 742
12.7%
i 691
11.8%
p 371
 
6.3%
u 320
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
N 757
52.3%
J 371
25.6%
O 320
22.1%
Space Separator
ValueCountFrequency (%)
1113
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7312
86.8%
Common 1113
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1128
15.4%
s 1113
15.2%
N 757
10.4%
o 757
10.4%
e 742
10.1%
a 742
10.1%
i 691
9.5%
J 371
 
5.1%
p 371
 
5.1%
O 320
 
4.4%
Common
ValueCountFrequency (%)
1113
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8425
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1128
13.4%
1113
13.2%
s 1113
13.2%
N 757
9.0%
o 757
9.0%
e 742
8.8%
a 742
8.8%
i 691
8.2%
J 371
 
4.4%
p 371
 
4.4%
Other values (2) 640
7.6%

acces_services _ Ville_q9
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size170.2 KiB
Plutôt en accord
670 
Tout à fait en accord
530 
Plutôt en désaccord
174 
Tout à fait en désaccord
71 
Ne s'applique pas
 
3

Length

Max length24
Median length21
Mean length18.584945
Min length16

Characters and Unicode

Total characters26911
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en désaccord
2nd rowPlutôt en désaccord
3rd rowTout à fait en accord
4th rowPlutôt en désaccord
5th rowPlutôt en accord

Common Values

ValueCountFrequency (%)
Plutôt en accord 670
46.3%
Tout à fait en accord 530
36.6%
Plutôt en désaccord 174
 
12.0%
Tout à fait en désaccord 71
 
4.9%
Ne s'applique pas 3
 
0.2%

Length

2023-06-18T04:18:24.178029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:24.469327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1445
26.1%
accord 1200
21.6%
plutôt 844
15.2%
tout 601
10.8%
à 601
10.8%
fait 601
10.8%
désaccord 245
 
4.4%
ne 3
 
0.1%
s'applique 3
 
0.1%
pas 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
4098
15.2%
t 2890
10.7%
c 2890
10.7%
a 2052
 
7.6%
o 2046
 
7.6%
d 1690
 
6.3%
e 1451
 
5.4%
u 1448
 
5.4%
r 1445
 
5.4%
n 1445
 
5.4%
Other values (13) 5456
20.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21362
79.4%
Space Separator 4098
 
15.2%
Uppercase Letter 1448
 
5.4%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2890
13.5%
c 2890
13.5%
a 2052
9.6%
o 2046
9.6%
d 1690
7.9%
e 1451
6.8%
u 1448
6.8%
r 1445
6.8%
n 1445
6.8%
l 847
 
4.0%
Other values (8) 3158
14.8%
Uppercase Letter
ValueCountFrequency (%)
P 844
58.3%
T 601
41.5%
N 3
 
0.2%
Space Separator
ValueCountFrequency (%)
4098
100.0%
Other Punctuation
ValueCountFrequency (%)
' 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22810
84.8%
Common 4101
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2890
12.7%
c 2890
12.7%
a 2052
9.0%
o 2046
9.0%
d 1690
 
7.4%
e 1451
 
6.4%
u 1448
 
6.3%
r 1445
 
6.3%
n 1445
 
6.3%
l 847
 
3.7%
Other values (11) 4606
20.2%
Common
ValueCountFrequency (%)
4098
99.9%
' 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25221
93.7%
None 1690
 
6.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4098
16.2%
t 2890
11.5%
c 2890
11.5%
a 2052
8.1%
o 2046
8.1%
d 1690
6.7%
e 1451
 
5.8%
u 1448
 
5.7%
r 1445
 
5.7%
n 1445
 
5.7%
Other values (10) 3766
14.9%
None
ValueCountFrequency (%)
ô 844
49.9%
à 601
35.6%
é 245
 
14.5%

milieu_et_qualite_ de_vie_q10_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1137
Missing (%)78.5%
Memory size64.9 KiB
Au travail
311 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3110
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAu travail
2nd rowAu travail
3rd rowAu travail
4th rowAu travail
5th rowAu travail

Common Values

ValueCountFrequency (%)
Au travail 311
 
21.5%
(Missing) 1137
78.5%

Length

2023-06-18T04:18:24.717025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:24.952474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
au 311
50.0%
travail 311
50.0%

Most occurring characters

ValueCountFrequency (%)
a 622
20.0%
A 311
10.0%
u 311
10.0%
311
10.0%
t 311
10.0%
r 311
10.0%
v 311
10.0%
i 311
10.0%
l 311
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2488
80.0%
Uppercase Letter 311
 
10.0%
Space Separator 311
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 622
25.0%
u 311
12.5%
t 311
12.5%
r 311
12.5%
v 311
12.5%
i 311
12.5%
l 311
12.5%
Uppercase Letter
ValueCountFrequency (%)
A 311
100.0%
Space Separator
ValueCountFrequency (%)
311
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2799
90.0%
Common 311
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 622
22.2%
A 311
11.1%
u 311
11.1%
t 311
11.1%
r 311
11.1%
v 311
11.1%
i 311
11.1%
l 311
11.1%
Common
ValueCountFrequency (%)
311
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 622
20.0%
A 311
10.0%
u 311
10.0%
311
10.0%
t 311
10.0%
r 311
10.0%
v 311
10.0%
i 311
10.0%
l 311
10.0%

milieu_et_qualite_de_vie_q10_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing1277
Missing (%)88.2%
Memory size64.7 KiB
Dans la recherche d'un logement
171 

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters5301
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDans la recherche d'un logement
2nd rowDans la recherche d'un logement
3rd rowDans la recherche d'un logement
4th rowDans la recherche d'un logement
5th rowDans la recherche d'un logement

Common Values

ValueCountFrequency (%)
Dans la recherche d'un logement 171
 
11.8%
(Missing) 1277
88.2%

Length

2023-06-18T04:18:25.154657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:25.400455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
dans 171
20.0%
la 171
20.0%
recherche 171
20.0%
d'un 171
20.0%
logement 171
20.0%

Most occurring characters

ValueCountFrequency (%)
e 855
16.1%
684
12.9%
n 513
9.7%
c 342
 
6.5%
l 342
 
6.5%
r 342
 
6.5%
a 342
 
6.5%
h 342
 
6.5%
u 171
 
3.2%
m 171
 
3.2%
Other values (7) 1197
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4275
80.6%
Space Separator 684
 
12.9%
Uppercase Letter 171
 
3.2%
Other Punctuation 171
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 855
20.0%
n 513
12.0%
c 342
 
8.0%
l 342
 
8.0%
r 342
 
8.0%
a 342
 
8.0%
h 342
 
8.0%
u 171
 
4.0%
m 171
 
4.0%
g 171
 
4.0%
Other values (4) 684
16.0%
Space Separator
ValueCountFrequency (%)
684
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 171
100.0%
Other Punctuation
ValueCountFrequency (%)
' 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4446
83.9%
Common 855
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 855
19.2%
n 513
11.5%
c 342
 
7.7%
l 342
 
7.7%
r 342
 
7.7%
a 342
 
7.7%
h 342
 
7.7%
u 171
 
3.8%
m 171
 
3.8%
g 171
 
3.8%
Other values (5) 855
19.2%
Common
ValueCountFrequency (%)
684
80.0%
' 171
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 855
16.1%
684
12.9%
n 513
9.7%
c 342
 
6.5%
l 342
 
6.5%
r 342
 
6.5%
a 342
 
6.5%
h 342
 
6.5%
u 171
 
3.2%
m 171
 
3.2%
Other values (7) 1197
22.6%

milieu_et_qualite_ de_vie_q10_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing1277
Missing (%)88.2%
Memory size64.4 KiB
Dans la recherche d'un emploi
171 

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters4959
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDans la recherche d'un emploi
2nd rowDans la recherche d'un emploi
3rd rowDans la recherche d'un emploi
4th rowDans la recherche d'un emploi
5th rowDans la recherche d'un emploi

Common Values

ValueCountFrequency (%)
Dans la recherche d'un emploi 171
 
11.8%
(Missing) 1277
88.2%

Length

2023-06-18T04:18:25.598641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:25.851466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
dans 171
20.0%
la 171
20.0%
recherche 171
20.0%
d'un 171
20.0%
emploi 171
20.0%

Most occurring characters

ValueCountFrequency (%)
684
13.8%
e 684
13.8%
c 342
 
6.9%
n 342
 
6.9%
l 342
 
6.9%
r 342
 
6.9%
a 342
 
6.9%
h 342
 
6.9%
u 171
 
3.4%
o 171
 
3.4%
Other values (7) 1197
24.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3933
79.3%
Space Separator 684
 
13.8%
Uppercase Letter 171
 
3.4%
Other Punctuation 171
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 684
17.4%
c 342
8.7%
n 342
8.7%
l 342
8.7%
r 342
8.7%
a 342
8.7%
h 342
8.7%
u 171
 
4.3%
o 171
 
4.3%
p 171
 
4.3%
Other values (4) 684
17.4%
Space Separator
ValueCountFrequency (%)
684
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 171
100.0%
Other Punctuation
ValueCountFrequency (%)
' 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4104
82.8%
Common 855
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 684
16.7%
c 342
 
8.3%
n 342
 
8.3%
l 342
 
8.3%
r 342
 
8.3%
a 342
 
8.3%
h 342
 
8.3%
u 171
 
4.2%
o 171
 
4.2%
p 171
 
4.2%
Other values (5) 855
20.8%
Common
ValueCountFrequency (%)
684
80.0%
' 171
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4959
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
684
13.8%
e 684
13.8%
c 342
 
6.9%
n 342
 
6.9%
l 342
 
6.9%
r 342
 
6.9%
a 342
 
6.9%
h 342
 
6.9%
u 171
 
3.4%
o 171
 
3.4%
Other values (7) 1197
24.1%

milieu_et_qualite_de_vie_q10_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing1042
Missing (%)72.0%
Memory size74.9 KiB
Dans les transports en commun
406 

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters11774
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDans les transports en commun
2nd rowDans les transports en commun
3rd rowDans les transports en commun
4th rowDans les transports en commun
5th rowDans les transports en commun

Common Values

ValueCountFrequency (%)
Dans les transports en commun 406
 
28.0%
(Missing) 1042
72.0%

Length

2023-06-18T04:18:26.049745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:26.289299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
dans 406
20.0%
les 406
20.0%
transports 406
20.0%
en 406
20.0%
commun 406
20.0%

Most occurring characters

ValueCountFrequency (%)
n 1624
13.8%
s 1624
13.8%
1624
13.8%
a 812
6.9%
e 812
6.9%
t 812
6.9%
r 812
6.9%
o 812
6.9%
m 812
6.9%
D 406
 
3.4%
Other values (4) 1624
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9744
82.8%
Space Separator 1624
 
13.8%
Uppercase Letter 406
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1624
16.7%
s 1624
16.7%
a 812
8.3%
e 812
8.3%
t 812
8.3%
r 812
8.3%
o 812
8.3%
m 812
8.3%
l 406
 
4.2%
p 406
 
4.2%
Other values (2) 812
8.3%
Space Separator
ValueCountFrequency (%)
1624
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 406
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10150
86.2%
Common 1624
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1624
16.0%
s 1624
16.0%
a 812
8.0%
e 812
8.0%
t 812
8.0%
r 812
8.0%
o 812
8.0%
m 812
8.0%
D 406
 
4.0%
l 406
 
4.0%
Other values (3) 1218
12.0%
Common
ValueCountFrequency (%)
1624
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11774
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1624
13.8%
s 1624
13.8%
1624
13.8%
a 812
6.9%
e 812
6.9%
t 812
6.9%
r 812
6.9%
o 812
6.9%
m 812
6.9%
D 406
 
3.4%
Other values (4) 1624
13.8%

milieu_et_qualite_de_vie_q10_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1220
Missing (%)84.3%
Memory size86.3 KiB
À l'école ou dans une institution académique
228 

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters10032
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ l'école ou dans une institution académique
2nd rowÀ l'école ou dans une institution académique
3rd rowÀ l'école ou dans une institution académique
4th rowÀ l'école ou dans une institution académique
5th rowÀ l'école ou dans une institution académique

Common Values

ValueCountFrequency (%)
À l'école ou dans une institution académique 228
 
15.7%
(Missing) 1220
84.3%

Length

2023-06-18T04:18:26.483660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:26.711819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
à 228
14.3%
l'école 228
14.3%
ou 228
14.3%
dans 228
14.3%
une 228
14.3%
institution 228
14.3%
académique 228
14.3%

Most occurring characters

ValueCountFrequency (%)
1368
13.6%
u 912
 
9.1%
n 912
 
9.1%
i 912
 
9.1%
t 684
 
6.8%
o 684
 
6.8%
e 684
 
6.8%
a 684
 
6.8%
l 456
 
4.5%
é 456
 
4.5%
Other values (7) 2280
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8208
81.8%
Space Separator 1368
 
13.6%
Uppercase Letter 228
 
2.3%
Other Punctuation 228
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 912
11.1%
n 912
11.1%
i 912
11.1%
t 684
8.3%
o 684
8.3%
e 684
8.3%
a 684
8.3%
l 456
 
5.6%
é 456
 
5.6%
c 456
 
5.6%
Other values (4) 1368
16.7%
Space Separator
ValueCountFrequency (%)
1368
100.0%
Uppercase Letter
ValueCountFrequency (%)
À 228
100.0%
Other Punctuation
ValueCountFrequency (%)
' 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8436
84.1%
Common 1596
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 912
10.8%
n 912
10.8%
i 912
10.8%
t 684
8.1%
o 684
8.1%
e 684
8.1%
a 684
8.1%
l 456
 
5.4%
é 456
 
5.4%
c 456
 
5.4%
Other values (5) 1596
18.9%
Common
ValueCountFrequency (%)
1368
85.7%
' 228
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9348
93.2%
None 684
 
6.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1368
14.6%
u 912
9.8%
n 912
9.8%
i 912
9.8%
t 684
7.3%
o 684
7.3%
e 684
7.3%
a 684
7.3%
l 456
 
4.9%
c 456
 
4.9%
Other values (5) 1596
17.1%
None
ValueCountFrequency (%)
é 456
66.7%
À 228
33.3%

milieu_et_qualite_de_vie_q10_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.9%
Missing1396
Missing (%)96.4%
Memory size62.1 KiB
Dans une bibliothèque municipale
52 

Length

Max length32
Median length32
Mean length32
Min length32

Characters and Unicode

Total characters1664
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDans une bibliothèque municipale
2nd rowDans une bibliothèque municipale
3rd rowDans une bibliothèque municipale
4th rowDans une bibliothèque municipale
5th rowDans une bibliothèque municipale

Common Values

ValueCountFrequency (%)
Dans une bibliothèque municipale 52
 
3.6%
(Missing) 1396
96.4%

Length

2023-06-18T04:18:26.902859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:27.128605image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
dans 52
25.0%
une 52
25.0%
bibliothèque 52
25.0%
municipale 52
25.0%

Most occurring characters

ValueCountFrequency (%)
i 208
12.5%
n 156
 
9.4%
156
 
9.4%
u 156
 
9.4%
e 156
 
9.4%
l 104
 
6.2%
b 104
 
6.2%
a 104
 
6.2%
è 52
 
3.1%
c 52
 
3.1%
Other values (8) 416
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1456
87.5%
Space Separator 156
 
9.4%
Uppercase Letter 52
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 208
14.3%
n 156
10.7%
u 156
10.7%
e 156
10.7%
l 104
 
7.1%
b 104
 
7.1%
a 104
 
7.1%
è 52
 
3.6%
c 52
 
3.6%
m 52
 
3.6%
Other values (6) 312
21.4%
Space Separator
ValueCountFrequency (%)
156
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1508
90.6%
Common 156
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 208
13.8%
n 156
10.3%
u 156
10.3%
e 156
10.3%
l 104
 
6.9%
b 104
 
6.9%
a 104
 
6.9%
è 52
 
3.4%
c 52
 
3.4%
m 52
 
3.4%
Other values (7) 364
24.1%
Common
ValueCountFrequency (%)
156
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1612
96.9%
None 52
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 208
12.9%
n 156
9.7%
156
9.7%
u 156
9.7%
e 156
9.7%
l 104
 
6.5%
b 104
 
6.5%
a 104
 
6.5%
c 52
 
3.2%
m 52
 
3.2%
Other values (7) 364
22.6%
None
ValueCountFrequency (%)
è 52
100.0%

milieu_et_qualite_de_vie_q10_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.9%
Missing1338
Missing (%)92.4%
Memory size63.2 KiB
Dans la recherche d'un service communautaire
110 

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters4840
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDans la recherche d'un service communautaire
2nd rowDans la recherche d'un service communautaire
3rd rowDans la recherche d'un service communautaire
4th rowDans la recherche d'un service communautaire
5th rowDans la recherche d'un service communautaire

Common Values

ValueCountFrequency (%)
Dans la recherche d'un service communautaire 110
 
7.6%
(Missing) 1338
92.4%

Length

2023-06-18T04:18:27.340523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:27.567272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
dans 110
16.7%
la 110
16.7%
recherche 110
16.7%
d'un 110
16.7%
service 110
16.7%
communautaire 110
16.7%

Most occurring characters

ValueCountFrequency (%)
e 660
13.6%
550
11.4%
r 440
9.1%
c 440
9.1%
a 440
9.1%
n 330
 
6.8%
u 330
 
6.8%
h 220
 
4.5%
s 220
 
4.5%
m 220
 
4.5%
Other values (8) 990
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4070
84.1%
Space Separator 550
 
11.4%
Uppercase Letter 110
 
2.3%
Other Punctuation 110
 
2.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 660
16.2%
r 440
10.8%
c 440
10.8%
a 440
10.8%
n 330
8.1%
u 330
8.1%
h 220
 
5.4%
s 220
 
5.4%
m 220
 
5.4%
i 220
 
5.4%
Other values (5) 550
13.5%
Space Separator
ValueCountFrequency (%)
550
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 110
100.0%
Other Punctuation
ValueCountFrequency (%)
' 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4180
86.4%
Common 660
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 660
15.8%
r 440
10.5%
c 440
10.5%
a 440
10.5%
n 330
7.9%
u 330
7.9%
h 220
 
5.3%
s 220
 
5.3%
m 220
 
5.3%
i 220
 
5.3%
Other values (6) 660
15.8%
Common
ValueCountFrequency (%)
550
83.3%
' 110
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 660
13.6%
550
11.4%
r 440
9.1%
c 440
9.1%
a 440
9.1%
n 330
 
6.8%
u 330
 
6.8%
h 220
 
4.5%
s 220
 
4.5%
m 220
 
4.5%
Other values (8) 990
20.5%

milieu_et_qualite_de_vie_q10_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1172
Missing (%)80.9%
Memory size62.6 KiB
Autre
276 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1380
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAutre
2nd rowAutre
3rd rowAutre
4th rowAutre
5th rowAutre

Common Values

ValueCountFrequency (%)
Autre 276
 
19.1%
(Missing) 1172
80.9%

Length

2023-06-18T04:18:27.757470image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:27.977194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
autre 276
100.0%

Most occurring characters

ValueCountFrequency (%)
A 276
20.0%
u 276
20.0%
t 276
20.0%
r 276
20.0%
e 276
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1104
80.0%
Uppercase Letter 276
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 276
25.0%
t 276
25.0%
r 276
25.0%
e 276
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1380
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 276
20.0%
u 276
20.0%
t 276
20.0%
r 276
20.0%
e 276
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1380
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 276
20.0%
u 276
20.0%
t 276
20.0%
r 276
20.0%
e 276
20.0%

milieu_et_qualite_de_vie_q10_9
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing752
Missing (%)51.9%
Memory size79.8 KiB
Ne s'applique pas
696 

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters11832
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNe s'applique pas
2nd rowNe s'applique pas
3rd rowNe s'applique pas
4th rowNe s'applique pas
5th rowNe s'applique pas

Common Values

ValueCountFrequency (%)
Ne s'applique pas 696
48.1%
(Missing) 752
51.9%

Length

2023-06-18T04:18:28.168128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:28.420800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ne 696
33.3%
s'applique 696
33.3%
pas 696
33.3%

Most occurring characters

ValueCountFrequency (%)
p 2088
17.6%
e 1392
11.8%
1392
11.8%
s 1392
11.8%
a 1392
11.8%
N 696
 
5.9%
' 696
 
5.9%
l 696
 
5.9%
i 696
 
5.9%
q 696
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9048
76.5%
Space Separator 1392
 
11.8%
Uppercase Letter 696
 
5.9%
Other Punctuation 696
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 2088
23.1%
e 1392
15.4%
s 1392
15.4%
a 1392
15.4%
l 696
 
7.7%
i 696
 
7.7%
q 696
 
7.7%
u 696
 
7.7%
Space Separator
ValueCountFrequency (%)
1392
100.0%
Uppercase Letter
ValueCountFrequency (%)
N 696
100.0%
Other Punctuation
ValueCountFrequency (%)
' 696
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9744
82.4%
Common 2088
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 2088
21.4%
e 1392
14.3%
s 1392
14.3%
a 1392
14.3%
N 696
 
7.1%
l 696
 
7.1%
i 696
 
7.1%
q 696
 
7.1%
u 696
 
7.1%
Common
ValueCountFrequency (%)
1392
66.7%
' 696
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
p 2088
17.6%
e 1392
11.8%
1392
11.8%
s 1392
11.8%
a 1392
11.8%
N 696
 
5.9%
' 696
 
5.9%
l 696
 
5.9%
i 696
 
5.9%
q 696
 
5.9%

milieu_et_qualite_de_vie_q11_1
Categorical

Distinct4
Distinct (%)0.3%
Missing5
Missing (%)0.3%
Memory size170.4 KiB
Plutôt en accord
618 
Plutôt en désaccord
405 
Tout à fait en accord
257 
Tout à fait en désaccord
163 

Length

Max length24
Median length21
Mean length18.636175
Min length16

Characters and Unicode

Total characters26892
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en désaccord
2nd rowTout à fait en accord
3rd rowPlutôt en désaccord
4th rowPlutôt en désaccord
5th rowTout à fait en désaccord

Common Values

ValueCountFrequency (%)
Plutôt en accord 618
42.7%
Plutôt en désaccord 405
28.0%
Tout à fait en accord 257
17.7%
Tout à fait en désaccord 163
 
11.3%
(Missing) 5
 
0.3%

Length

2023-06-18T04:18:28.628943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:28.922199image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1443
27.9%
plutôt 1023
19.8%
accord 875
16.9%
désaccord 568
 
11.0%
tout 420
 
8.1%
à 420
 
8.1%
fait 420
 
8.1%

Most occurring characters

ValueCountFrequency (%)
3726
13.9%
c 2886
10.7%
t 2886
10.7%
d 2011
 
7.5%
o 1863
 
6.9%
a 1863
 
6.9%
u 1443
 
5.4%
e 1443
 
5.4%
n 1443
 
5.4%
r 1443
 
5.4%
Other values (9) 5885
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21723
80.8%
Space Separator 3726
 
13.9%
Uppercase Letter 1443
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2886
13.3%
t 2886
13.3%
d 2011
9.3%
o 1863
8.6%
a 1863
8.6%
u 1443
6.6%
e 1443
6.6%
n 1443
6.6%
r 1443
6.6%
l 1023
 
4.7%
Other values (6) 3419
15.7%
Uppercase Letter
ValueCountFrequency (%)
P 1023
70.9%
T 420
29.1%
Space Separator
ValueCountFrequency (%)
3726
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23166
86.1%
Common 3726
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2886
12.5%
t 2886
12.5%
d 2011
8.7%
o 1863
 
8.0%
a 1863
 
8.0%
u 1443
 
6.2%
e 1443
 
6.2%
n 1443
 
6.2%
r 1443
 
6.2%
P 1023
 
4.4%
Other values (8) 4862
21.0%
Common
ValueCountFrequency (%)
3726
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24881
92.5%
None 2011
 
7.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3726
15.0%
c 2886
11.6%
t 2886
11.6%
d 2011
8.1%
o 1863
7.5%
a 1863
7.5%
u 1443
 
5.8%
e 1443
 
5.8%
n 1443
 
5.8%
r 1443
 
5.8%
Other values (6) 3874
15.6%
None
ValueCountFrequency (%)
ô 1023
50.9%
é 568
28.2%
à 420
20.9%

milieu_et_qualite_de_vie_q11_2
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing31
Missing (%)2.1%
Memory size169.2 KiB
Plutôt en désaccord
578 
Plutôt en accord
501 
Tout à fait en désaccord
214 
Tout à fait en accord
124 

Length

Max length24
Median length21
Mean length18.869442
Min length16

Characters and Unicode

Total characters26738
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTout à fait en désaccord
2nd rowPlutôt en désaccord
3rd rowPlutôt en désaccord
4th rowTout à fait en désaccord
5th rowPlutôt en désaccord

Common Values

ValueCountFrequency (%)
Plutôt en désaccord 578
39.9%
Plutôt en accord 501
34.6%
Tout à fait en désaccord 214
 
14.8%
Tout à fait en accord 124
 
8.6%
(Missing) 31
 
2.1%

Length

2023-06-18T04:18:29.182369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:29.483707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1417
28.8%
plutôt 1079
21.9%
désaccord 792
16.1%
accord 625
12.7%
tout 338
 
6.9%
à 338
 
6.9%
fait 338
 
6.9%

Most occurring characters

ValueCountFrequency (%)
3510
13.1%
t 2834
10.6%
c 2834
10.6%
d 2209
 
8.3%
o 1755
 
6.6%
a 1755
 
6.6%
u 1417
 
5.3%
e 1417
 
5.3%
n 1417
 
5.3%
r 1417
 
5.3%
Other values (9) 6173
23.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21811
81.6%
Space Separator 3510
 
13.1%
Uppercase Letter 1417
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2834
13.0%
c 2834
13.0%
d 2209
10.1%
o 1755
8.0%
a 1755
8.0%
u 1417
 
6.5%
e 1417
 
6.5%
n 1417
 
6.5%
r 1417
 
6.5%
ô 1079
 
4.9%
Other values (6) 3677
16.9%
Uppercase Letter
ValueCountFrequency (%)
P 1079
76.1%
T 338
 
23.9%
Space Separator
ValueCountFrequency (%)
3510
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23228
86.9%
Common 3510
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2834
12.2%
c 2834
12.2%
d 2209
9.5%
o 1755
 
7.6%
a 1755
 
7.6%
u 1417
 
6.1%
e 1417
 
6.1%
n 1417
 
6.1%
r 1417
 
6.1%
P 1079
 
4.6%
Other values (8) 5094
21.9%
Common
ValueCountFrequency (%)
3510
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24529
91.7%
None 2209
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3510
14.3%
t 2834
11.6%
c 2834
11.6%
d 2209
9.0%
o 1755
7.2%
a 1755
7.2%
u 1417
 
5.8%
e 1417
 
5.8%
n 1417
 
5.8%
r 1417
 
5.8%
Other values (6) 3964
16.2%
None
ValueCountFrequency (%)
ô 1079
48.8%
é 792
35.9%
à 338
 
15.3%

milieu_et_qualite_de_vie_q11_3
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing37
Missing (%)2.6%
Memory size169.4 KiB
Plutôt en désaccord
587 
Plutôt en accord
449 
Tout à fait en désaccord
248 
Tout à fait en accord
127 

Length

Max length24
Median length21
Mean length19.104181
Min length16

Characters and Unicode

Total characters26956
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en désaccord
2nd rowTout à fait en désaccord
3rd rowPlutôt en accord
4th rowPlutôt en désaccord
5th rowPlutôt en désaccord

Common Values

ValueCountFrequency (%)
Plutôt en désaccord 587
40.5%
Plutôt en accord 449
31.0%
Tout à fait en désaccord 248
17.1%
Tout à fait en accord 127
 
8.8%
(Missing) 37
 
2.6%

Length

2023-06-18T04:18:29.754858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:30.048717image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1411
28.3%
plutôt 1036
20.8%
désaccord 835
16.8%
accord 576
11.6%
tout 375
 
7.5%
à 375
 
7.5%
fait 375
 
7.5%

Most occurring characters

ValueCountFrequency (%)
3572
13.3%
t 2822
10.5%
c 2822
10.5%
d 2246
 
8.3%
o 1786
 
6.6%
a 1786
 
6.6%
u 1411
 
5.2%
e 1411
 
5.2%
n 1411
 
5.2%
r 1411
 
5.2%
Other values (9) 6278
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21973
81.5%
Space Separator 3572
 
13.3%
Uppercase Letter 1411
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2822
12.8%
c 2822
12.8%
d 2246
10.2%
o 1786
8.1%
a 1786
8.1%
u 1411
 
6.4%
e 1411
 
6.4%
n 1411
 
6.4%
r 1411
 
6.4%
ô 1036
 
4.7%
Other values (6) 3831
17.4%
Uppercase Letter
ValueCountFrequency (%)
P 1036
73.4%
T 375
 
26.6%
Space Separator
ValueCountFrequency (%)
3572
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23384
86.7%
Common 3572
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2822
12.1%
c 2822
12.1%
d 2246
9.6%
o 1786
 
7.6%
a 1786
 
7.6%
u 1411
 
6.0%
e 1411
 
6.0%
n 1411
 
6.0%
r 1411
 
6.0%
P 1036
 
4.4%
Other values (8) 5242
22.4%
Common
ValueCountFrequency (%)
3572
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24710
91.7%
None 2246
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3572
14.5%
t 2822
11.4%
c 2822
11.4%
d 2246
9.1%
o 1786
7.2%
a 1786
7.2%
u 1411
 
5.7%
e 1411
 
5.7%
n 1411
 
5.7%
r 1411
 
5.7%
Other values (6) 4032
16.3%
None
ValueCountFrequency (%)
ô 1036
46.1%
é 835
37.2%
à 375
 
16.7%

milieu_et_qualite_de_vie_q11_4
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing37
Missing (%)2.6%
Memory size170.3 KiB
Plutôt en désaccord
519 
Plutôt en accord
437 
Tout à fait en désaccord
336 
Tout à fait en accord
119 

Length

Max length24
Median length21
Mean length19.430191
Min length16

Characters and Unicode

Total characters27416
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en désaccord
2nd rowPlutôt en désaccord
3rd rowPlutôt en accord
4th rowTout à fait en désaccord
5th rowPlutôt en accord

Common Values

ValueCountFrequency (%)
Plutôt en désaccord 519
35.8%
Plutôt en accord 437
30.2%
Tout à fait en désaccord 336
23.2%
Tout à fait en accord 119
 
8.2%
(Missing) 37
 
2.6%

Length

2023-06-18T04:18:30.324401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:30.611479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1411
27.4%
plutôt 956
18.6%
désaccord 855
16.6%
accord 556
 
10.8%
tout 455
 
8.8%
à 455
 
8.8%
fait 455
 
8.8%

Most occurring characters

ValueCountFrequency (%)
3732
13.6%
t 2822
10.3%
c 2822
10.3%
d 2266
 
8.3%
o 1866
 
6.8%
a 1866
 
6.8%
u 1411
 
5.1%
e 1411
 
5.1%
n 1411
 
5.1%
r 1411
 
5.1%
Other values (9) 6398
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22273
81.2%
Space Separator 3732
 
13.6%
Uppercase Letter 1411
 
5.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2822
12.7%
c 2822
12.7%
d 2266
10.2%
o 1866
8.4%
a 1866
8.4%
u 1411
 
6.3%
e 1411
 
6.3%
n 1411
 
6.3%
r 1411
 
6.3%
ô 956
 
4.3%
Other values (6) 4031
18.1%
Uppercase Letter
ValueCountFrequency (%)
P 956
67.8%
T 455
32.2%
Space Separator
ValueCountFrequency (%)
3732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23684
86.4%
Common 3732
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2822
11.9%
c 2822
11.9%
d 2266
9.6%
o 1866
 
7.9%
a 1866
 
7.9%
u 1411
 
6.0%
e 1411
 
6.0%
n 1411
 
6.0%
r 1411
 
6.0%
P 956
 
4.0%
Other values (8) 5442
23.0%
Common
ValueCountFrequency (%)
3732
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25150
91.7%
None 2266
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3732
14.8%
t 2822
11.2%
c 2822
11.2%
d 2266
9.0%
o 1866
7.4%
a 1866
7.4%
u 1411
 
5.6%
e 1411
 
5.6%
n 1411
 
5.6%
r 1411
 
5.6%
Other values (6) 4132
16.4%
None
ValueCountFrequency (%)
ô 956
42.2%
é 855
37.7%
à 455
20.1%

milieu_et_qualite_de_vie_q11_5
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing38
Missing (%)2.6%
Memory size168.9 KiB
Plutôt en désaccord
560 
Plutôt en accord
499 
Tout à fait en désaccord
246 
Tout à fait en accord
105 

Length

Max length24
Median length21
Mean length18.959574
Min length16

Characters and Unicode

Total characters26733
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTout à fait en désaccord
2nd rowTout à fait en désaccord
3rd rowTout à fait en désaccord
4th rowTout à fait en désaccord
5th rowPlutôt en accord

Common Values

ValueCountFrequency (%)
Plutôt en désaccord 560
38.7%
Plutôt en accord 499
34.5%
Tout à fait en désaccord 246
17.0%
Tout à fait en accord 105
 
7.3%
(Missing) 38
 
2.6%

Length

2023-06-18T04:18:30.872974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:31.155688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1410
28.6%
plutôt 1059
21.5%
désaccord 806
16.3%
accord 604
12.2%
tout 351
 
7.1%
à 351
 
7.1%
fait 351
 
7.1%

Most occurring characters

ValueCountFrequency (%)
3522
13.2%
t 2820
10.5%
c 2820
10.5%
d 2216
 
8.3%
o 1761
 
6.6%
a 1761
 
6.6%
u 1410
 
5.3%
e 1410
 
5.3%
n 1410
 
5.3%
r 1410
 
5.3%
Other values (9) 6193
23.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21801
81.6%
Space Separator 3522
 
13.2%
Uppercase Letter 1410
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2820
12.9%
c 2820
12.9%
d 2216
10.2%
o 1761
8.1%
a 1761
8.1%
u 1410
 
6.5%
e 1410
 
6.5%
n 1410
 
6.5%
r 1410
 
6.5%
ô 1059
 
4.9%
Other values (6) 3724
17.1%
Uppercase Letter
ValueCountFrequency (%)
P 1059
75.1%
T 351
 
24.9%
Space Separator
ValueCountFrequency (%)
3522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23211
86.8%
Common 3522
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2820
12.1%
c 2820
12.1%
d 2216
9.5%
o 1761
 
7.6%
a 1761
 
7.6%
u 1410
 
6.1%
e 1410
 
6.1%
n 1410
 
6.1%
r 1410
 
6.1%
P 1059
 
4.6%
Other values (8) 5134
22.1%
Common
ValueCountFrequency (%)
3522
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24517
91.7%
None 2216
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3522
14.4%
t 2820
11.5%
c 2820
11.5%
d 2216
9.0%
o 1761
7.2%
a 1761
7.2%
u 1410
 
5.8%
e 1410
 
5.8%
n 1410
 
5.8%
r 1410
 
5.8%
Other values (6) 3977
16.2%
None
ValueCountFrequency (%)
ô 1059
47.8%
é 806
36.4%
à 351
 
15.8%

milieu_et_qualité_de_vie_q11_6
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing42
Missing (%)2.9%
Memory size172.0 KiB
Plutôt en désaccord
569 
Tout à fait en désaccord
463 
Plutôt en accord
294 
Tout à fait en accord
80 

Length

Max length24
Median length21
Mean length20.133001
Min length16

Characters and Unicode

Total characters28307
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTout à fait en désaccord
2nd rowTout à fait en désaccord
3rd rowTout à fait en désaccord
4th rowTout à fait en désaccord
5th rowPlutôt en désaccord

Common Values

ValueCountFrequency (%)
Plutôt en désaccord 569
39.3%
Tout à fait en désaccord 463
32.0%
Plutôt en accord 294
20.3%
Tout à fait en accord 80
 
5.5%
(Missing) 42
 
2.9%

Length

2023-06-18T04:18:31.429415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:31.856074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1406
26.5%
désaccord 1032
19.5%
plutôt 863
16.3%
tout 543
 
10.2%
à 543
 
10.2%
fait 543
 
10.2%
accord 374
 
7.1%

Most occurring characters

ValueCountFrequency (%)
3898
13.8%
c 2812
9.9%
t 2812
9.9%
d 2438
 
8.6%
o 1949
 
6.9%
a 1949
 
6.9%
u 1406
 
5.0%
r 1406
 
5.0%
e 1406
 
5.0%
n 1406
 
5.0%
Other values (9) 6825
24.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23003
81.3%
Space Separator 3898
 
13.8%
Uppercase Letter 1406
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2812
12.2%
t 2812
12.2%
d 2438
10.6%
o 1949
8.5%
a 1949
8.5%
u 1406
 
6.1%
r 1406
 
6.1%
e 1406
 
6.1%
n 1406
 
6.1%
é 1032
 
4.5%
Other values (6) 4387
19.1%
Uppercase Letter
ValueCountFrequency (%)
P 863
61.4%
T 543
38.6%
Space Separator
ValueCountFrequency (%)
3898
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24409
86.2%
Common 3898
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2812
11.5%
t 2812
11.5%
d 2438
10.0%
o 1949
 
8.0%
a 1949
 
8.0%
u 1406
 
5.8%
r 1406
 
5.8%
e 1406
 
5.8%
n 1406
 
5.8%
é 1032
 
4.2%
Other values (8) 5793
23.7%
Common
ValueCountFrequency (%)
3898
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25869
91.4%
None 2438
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3898
15.1%
c 2812
10.9%
t 2812
10.9%
d 2438
9.4%
o 1949
7.5%
a 1949
7.5%
u 1406
 
5.4%
r 1406
 
5.4%
e 1406
 
5.4%
n 1406
 
5.4%
Other values (6) 4387
17.0%
None
ValueCountFrequency (%)
é 1032
42.3%
ô 863
35.4%
à 543
22.3%

milieu_et_qualite_de_vie_q11_7
Categorical

Distinct4
Distinct (%)0.3%
Missing11
Missing (%)0.8%
Memory size169.5 KiB
Plutôt en accord
637 
Plutôt en désaccord
386 
Tout à fait en accord
284 
Tout à fait en désaccord
130 

Length

Max length24
Median length21
Mean length18.517745
Min length16

Characters and Unicode

Total characters26610
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en accord
2nd rowPlutôt en accord
3rd rowTout à fait en désaccord
4th rowPlutôt en accord
5th rowPlutôt en accord

Common Values

ValueCountFrequency (%)
Plutôt en accord 637
44.0%
Plutôt en désaccord 386
26.7%
Tout à fait en accord 284
19.6%
Tout à fait en désaccord 130
 
9.0%
(Missing) 11
 
0.8%

Length

2023-06-18T04:18:32.335650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:32.777571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1437
28.0%
plutôt 1023
19.9%
accord 921
17.9%
désaccord 516
 
10.0%
tout 414
 
8.1%
à 414
 
8.1%
fait 414
 
8.1%

Most occurring characters

ValueCountFrequency (%)
3702
13.9%
c 2874
10.8%
t 2874
10.8%
d 1953
 
7.3%
o 1851
 
7.0%
a 1851
 
7.0%
u 1437
 
5.4%
e 1437
 
5.4%
n 1437
 
5.4%
r 1437
 
5.4%
Other values (9) 5757
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21471
80.7%
Space Separator 3702
 
13.9%
Uppercase Letter 1437
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2874
13.4%
t 2874
13.4%
d 1953
9.1%
o 1851
8.6%
a 1851
8.6%
u 1437
6.7%
e 1437
6.7%
n 1437
6.7%
r 1437
6.7%
l 1023
 
4.8%
Other values (6) 3297
15.4%
Uppercase Letter
ValueCountFrequency (%)
P 1023
71.2%
T 414
28.8%
Space Separator
ValueCountFrequency (%)
3702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22908
86.1%
Common 3702
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2874
12.5%
t 2874
12.5%
d 1953
8.5%
o 1851
 
8.1%
a 1851
 
8.1%
u 1437
 
6.3%
e 1437
 
6.3%
n 1437
 
6.3%
r 1437
 
6.3%
P 1023
 
4.5%
Other values (8) 4734
20.7%
Common
ValueCountFrequency (%)
3702
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24657
92.7%
None 1953
 
7.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3702
15.0%
c 2874
11.7%
t 2874
11.7%
d 1953
7.9%
o 1851
7.5%
a 1851
7.5%
u 1437
 
5.8%
e 1437
 
5.8%
n 1437
 
5.8%
r 1437
 
5.8%
Other values (6) 3804
15.4%
None
ValueCountFrequency (%)
ô 1023
52.4%
é 516
26.4%
à 414
21.2%

milieu_et_qualite_de_vie_q11_8
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)0.3%
Missing22
Missing (%)1.5%
Memory size168.5 KiB
Plutôt en accord
643 
Plutôt en désaccord
375 
Tout à fait en accord
290 
Tout à fait en désaccord
118 

Length

Max length24
Median length21
Mean length18.467742
Min length16

Characters and Unicode

Total characters26335
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPlutôt en accord
2nd rowPlutôt en accord
3rd rowPlutôt en accord
4th rowPlutôt en désaccord
5th rowPlutôt en désaccord

Common Values

ValueCountFrequency (%)
Plutôt en accord 643
44.4%
Plutôt en désaccord 375
25.9%
Tout à fait en accord 290
20.0%
Tout à fait en désaccord 118
 
8.1%
(Missing) 22
 
1.5%

Length

2023-06-18T04:18:33.228205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:33.736042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
en 1426
28.0%
plutôt 1018
20.0%
accord 933
18.3%
désaccord 493
 
9.7%
tout 408
 
8.0%
à 408
 
8.0%
fait 408
 
8.0%

Most occurring characters

ValueCountFrequency (%)
3668
13.9%
c 2852
10.8%
t 2852
10.8%
d 1919
 
7.3%
o 1834
 
7.0%
a 1834
 
7.0%
u 1426
 
5.4%
e 1426
 
5.4%
n 1426
 
5.4%
r 1426
 
5.4%
Other values (9) 5672
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21241
80.7%
Space Separator 3668
 
13.9%
Uppercase Letter 1426
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 2852
13.4%
t 2852
13.4%
d 1919
9.0%
o 1834
8.6%
a 1834
8.6%
u 1426
6.7%
e 1426
6.7%
n 1426
6.7%
r 1426
6.7%
l 1018
 
4.8%
Other values (6) 3228
15.2%
Uppercase Letter
ValueCountFrequency (%)
P 1018
71.4%
T 408
28.6%
Space Separator
ValueCountFrequency (%)
3668
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22667
86.1%
Common 3668
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 2852
12.6%
t 2852
12.6%
d 1919
8.5%
o 1834
 
8.1%
a 1834
 
8.1%
u 1426
 
6.3%
e 1426
 
6.3%
n 1426
 
6.3%
r 1426
 
6.3%
P 1018
 
4.5%
Other values (8) 4654
20.5%
Common
ValueCountFrequency (%)
3668
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24416
92.7%
None 1919
 
7.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3668
15.0%
c 2852
11.7%
t 2852
11.7%
d 1919
7.9%
o 1834
7.5%
a 1834
7.5%
u 1426
 
5.8%
e 1426
 
5.8%
n 1426
 
5.8%
r 1426
 
5.8%
Other values (6) 3753
15.4%
None
ValueCountFrequency (%)
ô 1018
53.0%
é 493
25.7%
à 408
21.3%

milieu_et_qualite_de_vie_q12
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
1007 
Oui
441 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowOui
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1007
69.5%
Oui 441
30.5%

Length

2023-06-18T04:18:34.065686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:34.539912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1007
69.5%
oui 441
30.5%

Most occurring characters

ValueCountFrequency (%)
N 1007
23.2%
o 1007
23.2%
n 1007
23.2%
O 441
10.2%
u 441
10.2%
i 441
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1007
34.8%
n 1007
34.8%
u 441
15.2%
i 441
15.2%
Uppercase Letter
ValueCountFrequency (%)
N 1007
69.5%
O 441
30.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1007
23.2%
o 1007
23.2%
n 1007
23.2%
O 441
10.2%
u 441
10.2%
i 441
10.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1007
23.2%
o 1007
23.2%
n 1007
23.2%
O 441
10.2%
u 441
10.2%
i 441
10.2%

securité_dans_espace_public_q13
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size100.3 KiB
Oui, rarement
522 
Oui, quelquefois
513 
Non, jamais
259 
Oui, souvent
148 
Ne s’applique pas
 
6

Length

Max length17
Median length16
Mean length13.619475
Min length11

Characters and Unicode

Total characters19721
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui, quelquefois
2nd rowOui, souvent
3rd rowOui, rarement
4th rowOui, quelquefois
5th rowOui, quelquefois

Common Values

ValueCountFrequency (%)
Oui, rarement 522
36.0%
Oui, quelquefois 513
35.4%
Non, jamais 259
17.9%
Oui, souvent 148
 
10.2%
Ne s’applique pas 6
 
0.4%

Length

2023-06-18T04:18:34.998948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:35.282871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
oui 1183
40.8%
rarement 522
18.0%
quelquefois 513
17.7%
non 259
 
8.9%
jamais 259
 
8.9%
souvent 148
 
5.1%
ne 6
 
0.2%
s’applique 6
 
0.2%
pas 6
 
0.2%

Most occurring characters

ValueCountFrequency (%)
u 2363
12.0%
e 2230
11.3%
i 1961
 
9.9%
1454
 
7.4%
, 1442
 
7.3%
O 1183
 
6.0%
a 1052
 
5.3%
r 1044
 
5.3%
q 1032
 
5.2%
s 932
 
4.7%
Other values (11) 5028
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15371
77.9%
Space Separator 1454
 
7.4%
Uppercase Letter 1448
 
7.3%
Other Punctuation 1442
 
7.3%
Final Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 2363
15.4%
e 2230
14.5%
i 1961
12.8%
a 1052
6.8%
r 1044
6.8%
q 1032
6.7%
s 932
 
6.1%
n 929
 
6.0%
o 920
 
6.0%
m 781
 
5.1%
Other values (6) 2127
13.8%
Uppercase Letter
ValueCountFrequency (%)
O 1183
81.7%
N 265
 
18.3%
Space Separator
ValueCountFrequency (%)
1454
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1442
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16819
85.3%
Common 2902
 
14.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 2363
14.0%
e 2230
13.3%
i 1961
11.7%
O 1183
 
7.0%
a 1052
 
6.3%
r 1044
 
6.2%
q 1032
 
6.1%
s 932
 
5.5%
n 929
 
5.5%
o 920
 
5.5%
Other values (8) 3173
18.9%
Common
ValueCountFrequency (%)
1454
50.1%
, 1442
49.7%
’ 6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19715
> 99.9%
Punctuation 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 2363
12.0%
e 2230
11.3%
i 1961
 
9.9%
1454
 
7.4%
, 1442
 
7.3%
O 1183
 
6.0%
a 1052
 
5.3%
r 1044
 
5.3%
q 1032
 
5.2%
s 932
 
4.7%
Other values (10) 5022
25.5%
Punctuation
ValueCountFrequency (%)
’ 6
100.0%

securité_dans_espace_public_q14_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing623
Missing (%)43.0%
Memory size206.5 KiB
Harcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)
825 

Length

Max length71
Median length71
Mean length71
Min length71

Characters and Unicode

Total characters58575
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)
2nd rowHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)
3rd rowHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)
4th rowHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)
5th rowHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)

Common Values

ValueCountFrequency (%)
Harcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation) 825
57.0%
(Missing) 623
43.0%

Length

2023-06-18T04:18:35.526994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:35.767465image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
harcèlement 825
11.1%
verbal 825
11.1%
ex 825
11.1%
insulte 825
11.1%
blague 825
11.1%
de 825
11.1%
mauvais 825
11.1%
goût 825
11.1%
intimidation 825
11.1%

Most occurring characters

ValueCountFrequency (%)
6600
 
11.3%
e 5775
 
9.9%
a 4950
 
8.5%
i 4950
 
8.5%
t 4125
 
7.0%
l 3300
 
5.6%
n 3300
 
5.6%
m 2475
 
4.2%
u 2475
 
4.2%
, 1650
 
2.8%
Other values (16) 18975
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46200
78.9%
Space Separator 6600
 
11.3%
Other Punctuation 3300
 
5.6%
Uppercase Letter 825
 
1.4%
Open Punctuation 825
 
1.4%
Close Punctuation 825
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5775
12.5%
a 4950
10.7%
i 4950
10.7%
t 4125
 
8.9%
l 3300
 
7.1%
n 3300
 
7.1%
m 2475
 
5.4%
u 2475
 
5.4%
g 1650
 
3.6%
d 1650
 
3.6%
Other values (9) 11550
25.0%
Other Punctuation
ValueCountFrequency (%)
, 1650
50.0%
: 825
25.0%
. 825
25.0%
Space Separator
ValueCountFrequency (%)
6600
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 825
100.0%
Open Punctuation
ValueCountFrequency (%)
( 825
100.0%
Close Punctuation
ValueCountFrequency (%)
) 825
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 47025
80.3%
Common 11550
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5775
12.3%
a 4950
 
10.5%
i 4950
 
10.5%
t 4125
 
8.8%
l 3300
 
7.0%
n 3300
 
7.0%
m 2475
 
5.3%
u 2475
 
5.3%
g 1650
 
3.5%
d 1650
 
3.5%
Other values (10) 12375
26.3%
Common
ValueCountFrequency (%)
6600
57.1%
, 1650
 
14.3%
( 825
 
7.1%
: 825
 
7.1%
. 825
 
7.1%
) 825
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56925
97.2%
None 1650
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6600
 
11.6%
e 5775
 
10.1%
a 4950
 
8.7%
i 4950
 
8.7%
t 4125
 
7.2%
l 3300
 
5.8%
n 3300
 
5.8%
m 2475
 
4.3%
u 2475
 
4.3%
, 1650
 
2.9%
Other values (14) 17325
30.4%
None
ValueCountFrequency (%)
û 825
50.0%
è 825
50.0%

securité_dans_espace_public_q14_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing1017
Missing (%)70.2%
Memory size166.1 KiB
Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)
431 

Length

Max length106
Median length106
Mean length106
Min length106

Characters and Unicode

Total characters45686
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAvance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)
2nd rowAvance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)
3rd rowAvance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)
4th rowAvance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)
5th rowAvance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)

Common Values

ValueCountFrequency (%)
Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée) 431
29.8%
(Missing) 1017
70.2%

Length

2023-06-18T04:18:35.968747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:36.205480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
avance 862
13.3%
non 862
13.3%
désirée 862
13.3%
sexuelle 431
6.7%
ex 431
6.7%
verbale 431
6.7%
ou 431
6.7%
proposition 431
6.7%
insistante 431
6.7%
à 431
6.7%
Other values (2) 862
13.3%

Most occurring characters

ValueCountFrequency (%)
e 6034
13.2%
6034
13.2%
n 3879
 
8.5%
a 3017
 
6.6%
s 3017
 
6.6%
r 2586
 
5.7%
i 2586
 
5.7%
o 2586
 
5.7%
t 1724
 
3.8%
é 1724
 
3.8%
Other values (15) 12499
27.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37497
82.1%
Space Separator 6034
 
13.2%
Other Punctuation 862
 
1.9%
Uppercase Letter 431
 
0.9%
Open Punctuation 431
 
0.9%
Close Punctuation 431
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6034
16.1%
n 3879
10.3%
a 3017
 
8.0%
s 3017
 
8.0%
r 2586
 
6.9%
i 2586
 
6.9%
o 2586
 
6.9%
t 1724
 
4.6%
é 1724
 
4.6%
c 1724
 
4.6%
Other values (9) 8620
23.0%
Other Punctuation
ValueCountFrequency (%)
: 431
50.0%
. 431
50.0%
Space Separator
ValueCountFrequency (%)
6034
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 431
100.0%
Open Punctuation
ValueCountFrequency (%)
( 431
100.0%
Close Punctuation
ValueCountFrequency (%)
) 431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 37928
83.0%
Common 7758
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6034
15.9%
n 3879
10.2%
a 3017
 
8.0%
s 3017
 
8.0%
r 2586
 
6.8%
i 2586
 
6.8%
o 2586
 
6.8%
t 1724
 
4.5%
é 1724
 
4.5%
c 1724
 
4.5%
Other values (10) 9051
23.9%
Common
ValueCountFrequency (%)
6034
77.8%
: 431
 
5.6%
. 431
 
5.6%
( 431
 
5.6%
) 431
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43100
94.3%
None 2586
 
5.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 6034
14.0%
6034
14.0%
n 3879
 
9.0%
a 3017
 
7.0%
s 3017
 
7.0%
r 2586
 
6.0%
i 2586
 
6.0%
o 2586
 
6.0%
t 1724
 
4.0%
c 1724
 
4.0%
Other values (12) 9913
23.0%
None
ValueCountFrequency (%)
é 1724
66.7%
è 431
 
16.7%
à 431
 
16.7%

securité_dans_espace_public_q14_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1212
Missing (%)83.7%
Memory size64.5 KiB
Cyberintimidation
236 

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters4012
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCyberintimidation
2nd rowCyberintimidation
3rd rowCyberintimidation
4th rowCyberintimidation
5th rowCyberintimidation

Common Values

ValueCountFrequency (%)
Cyberintimidation 236
 
16.3%
(Missing) 1212
83.7%

Length

2023-06-18T04:18:36.411250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:36.638157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
cyberintimidation 236
100.0%

Most occurring characters

ValueCountFrequency (%)
i 944
23.5%
n 472
11.8%
t 472
11.8%
C 236
 
5.9%
y 236
 
5.9%
b 236
 
5.9%
e 236
 
5.9%
r 236
 
5.9%
m 236
 
5.9%
d 236
 
5.9%
Other values (2) 472
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3776
94.1%
Uppercase Letter 236
 
5.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 944
25.0%
n 472
12.5%
t 472
12.5%
y 236
 
6.2%
b 236
 
6.2%
e 236
 
6.2%
r 236
 
6.2%
m 236
 
6.2%
d 236
 
6.2%
a 236
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
C 236
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4012
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 944
23.5%
n 472
11.8%
t 472
11.8%
C 236
 
5.9%
y 236
 
5.9%
b 236
 
5.9%
e 236
 
5.9%
r 236
 
5.9%
m 236
 
5.9%
d 236
 
5.9%
Other values (2) 472
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4012
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 944
23.5%
n 472
11.8%
t 472
11.8%
C 236
 
5.9%
y 236
 
5.9%
b 236
 
5.9%
e 236
 
5.9%
r 236
 
5.9%
m 236
 
5.9%
d 236
 
5.9%
Other values (2) 472
11.8%

securité_dans_espace_public_q14_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing1350
Missing (%)93.2%
Memory size81.7 KiB
Agression physique (ex.: geste portant atteinte à l’intégrité physique)
98 

Length

Max length71
Median length71
Mean length71
Min length71

Characters and Unicode

Total characters6958
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAgression physique (ex.: geste portant atteinte à l’intégrité physique)
2nd rowAgression physique (ex.: geste portant atteinte à l’intégrité physique)
3rd rowAgression physique (ex.: geste portant atteinte à l’intégrité physique)
4th rowAgression physique (ex.: geste portant atteinte à l’intégrité physique)
5th rowAgression physique (ex.: geste portant atteinte à l’intégrité physique)

Common Values

ValueCountFrequency (%)
Agression physique (ex.: geste portant atteinte à l’intégrité physique) 98
 
6.8%
(Missing) 1350
93.2%

Length

2023-06-18T04:18:36.826653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:37.041808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
physique 196
22.2%
agression 98
11.1%
ex 98
11.1%
geste 98
11.1%
portant 98
11.1%
atteinte 98
11.1%
à 98
11.1%
l’intégrité 98
11.1%

Most occurring characters

ValueCountFrequency (%)
t 784
 
11.3%
e 784
 
11.3%
784
 
11.3%
i 588
 
8.5%
s 490
 
7.0%
n 392
 
5.6%
g 294
 
4.2%
p 294
 
4.2%
r 294
 
4.2%
o 196
 
2.8%
Other values (15) 2058
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5586
80.3%
Space Separator 784
 
11.3%
Other Punctuation 196
 
2.8%
Final Punctuation 98
 
1.4%
Uppercase Letter 98
 
1.4%
Open Punctuation 98
 
1.4%
Close Punctuation 98
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 784
14.0%
e 784
14.0%
i 588
10.5%
s 490
 
8.8%
n 392
 
7.0%
g 294
 
5.3%
p 294
 
5.3%
r 294
 
5.3%
o 196
 
3.5%
a 196
 
3.5%
Other values (8) 1274
22.8%
Other Punctuation
ValueCountFrequency (%)
: 98
50.0%
. 98
50.0%
Space Separator
ValueCountFrequency (%)
784
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 98
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5684
81.7%
Common 1274
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 784
13.8%
e 784
13.8%
i 588
10.3%
s 490
 
8.6%
n 392
 
6.9%
g 294
 
5.2%
p 294
 
5.2%
r 294
 
5.2%
o 196
 
3.4%
a 196
 
3.4%
Other values (9) 1372
24.1%
Common
ValueCountFrequency (%)
784
61.5%
’ 98
 
7.7%
: 98
 
7.7%
. 98
 
7.7%
( 98
 
7.7%
) 98
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6566
94.4%
None 294
 
4.2%
Punctuation 98
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 784
11.9%
e 784
11.9%
784
11.9%
i 588
 
9.0%
s 490
 
7.5%
n 392
 
6.0%
g 294
 
4.5%
p 294
 
4.5%
r 294
 
4.5%
o 196
 
3.0%
Other values (12) 1666
25.4%
None
ValueCountFrequency (%)
é 196
66.7%
à 98
33.3%
Punctuation
ValueCountFrequency (%)
’ 98
100.0%

securité_dans_espace_public_q14_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing1352
Missing (%)93.4%
Memory size65.1 KiB
Agression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)
96 

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters7008
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAgression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)
2nd rowAgression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)
3rd rowAgression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)
4th rowAgression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)
5th rowAgression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)

Common Values

ValueCountFrequency (%)
Agression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence) 96
 
6.6%
(Missing) 1352
93.4%

Length

2023-06-18T04:18:37.224816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:37.464960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
agression 96
9.1%
sexuelle 96
9.1%
ex 96
9.1%
acte 96
9.1%
sexuel 96
9.1%
non 96
9.1%
consenti 96
9.1%
avec 96
9.1%
ou 96
9.1%
sans 96
9.1%

Most occurring characters

ValueCountFrequency (%)
e 1152
16.4%
960
13.7%
s 672
9.6%
n 672
9.6%
o 480
 
6.8%
l 384
 
5.5%
c 384
 
5.5%
u 288
 
4.1%
a 288
 
4.1%
i 288
 
4.1%
Other values (11) 1440
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5472
78.1%
Space Separator 960
 
13.7%
Other Punctuation 288
 
4.1%
Uppercase Letter 96
 
1.4%
Open Punctuation 96
 
1.4%
Close Punctuation 96
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1152
21.1%
s 672
12.3%
n 672
12.3%
o 480
8.8%
l 384
 
7.0%
c 384
 
7.0%
u 288
 
5.3%
a 288
 
5.3%
i 288
 
5.3%
x 288
 
5.3%
Other values (4) 576
10.5%
Other Punctuation
ValueCountFrequency (%)
, 96
33.3%
: 96
33.3%
. 96
33.3%
Space Separator
ValueCountFrequency (%)
960
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 96
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5568
79.5%
Common 1440
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1152
20.7%
s 672
12.1%
n 672
12.1%
o 480
8.6%
l 384
 
6.9%
c 384
 
6.9%
u 288
 
5.2%
a 288
 
5.2%
i 288
 
5.2%
x 288
 
5.2%
Other values (5) 672
12.1%
Common
ValueCountFrequency (%)
960
66.7%
, 96
 
6.7%
: 96
 
6.7%
. 96
 
6.7%
( 96
 
6.7%
) 96
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1152
16.4%
960
13.7%
s 672
9.6%
n 672
9.6%
o 480
 
6.8%
l 384
 
5.5%
c 384
 
5.5%
u 288
 
4.1%
a 288
 
4.1%
i 288
 
4.1%
Other values (11) 1440
20.5%

securité_dans_espace_public_q14_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing1252
Missing (%)86.5%
Memory size65.1 KiB
Menace de violence physique
196 

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters5292
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMenace de violence physique
2nd rowMenace de violence physique
3rd rowMenace de violence physique
4th rowMenace de violence physique
5th rowMenace de violence physique

Common Values

ValueCountFrequency (%)
Menace de violence physique 196
 
13.5%
(Missing) 1252
86.5%

Length

2023-06-18T04:18:37.645559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:38.255887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
menace 196
25.0%
de 196
25.0%
violence 196
25.0%
physique 196
25.0%

Most occurring characters

ValueCountFrequency (%)
e 1176
22.2%
588
11.1%
i 392
 
7.4%
n 392
 
7.4%
c 392
 
7.4%
p 196
 
3.7%
q 196
 
3.7%
s 196
 
3.7%
y 196
 
3.7%
h 196
 
3.7%
Other values (7) 1372
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4508
85.2%
Space Separator 588
 
11.1%
Uppercase Letter 196
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1176
26.1%
i 392
 
8.7%
n 392
 
8.7%
c 392
 
8.7%
p 196
 
4.3%
q 196
 
4.3%
s 196
 
4.3%
y 196
 
4.3%
h 196
 
4.3%
l 196
 
4.3%
Other values (5) 980
21.7%
Space Separator
ValueCountFrequency (%)
588
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4704
88.9%
Common 588
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1176
25.0%
i 392
 
8.3%
n 392
 
8.3%
c 392
 
8.3%
p 196
 
4.2%
q 196
 
4.2%
s 196
 
4.2%
y 196
 
4.2%
h 196
 
4.2%
M 196
 
4.2%
Other values (6) 1176
25.0%
Common
ValueCountFrequency (%)
588
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1176
22.2%
588
11.1%
i 392
 
7.4%
n 392
 
7.4%
c 392
 
7.4%
p 196
 
3.7%
q 196
 
3.7%
s 196
 
3.7%
y 196
 
3.7%
h 196
 
3.7%
Other values (7) 1372
25.9%

securité_dans_espace_public_q14_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.7%
Missing1390
Missing (%)96.0%
Memory size70.4 KiB
Refus d’être servi dans un commerce (magasin, restaurant ou café)
58 

Length

Max length65
Median length65
Mean length65
Min length65

Characters and Unicode

Total characters3770
Distinct characters23
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRefus d’être servi dans un commerce (magasin, restaurant ou café)
2nd rowRefus d’être servi dans un commerce (magasin, restaurant ou café)
3rd rowRefus d’être servi dans un commerce (magasin, restaurant ou café)
4th rowRefus d’être servi dans un commerce (magasin, restaurant ou café)
5th rowRefus d’être servi dans un commerce (magasin, restaurant ou café)

Common Values

ValueCountFrequency (%)
Refus d’être servi dans un commerce (magasin, restaurant ou café) 58
 
4.0%
(Missing) 1390
96.0%

Length

2023-06-18T04:18:38.574201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:38.810308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
refus 58
10.0%
d’être 58
10.0%
servi 58
10.0%
dans 58
10.0%
un 58
10.0%
commerce 58
10.0%
magasin 58
10.0%
restaurant 58
10.0%
ou 58
10.0%
café 58
10.0%

Most occurring characters

ValueCountFrequency (%)
522
13.8%
a 348
 
9.2%
e 348
 
9.2%
r 290
 
7.7%
s 290
 
7.7%
u 232
 
6.2%
n 232
 
6.2%
t 174
 
4.6%
c 174
 
4.6%
m 174
 
4.6%
Other values (13) 986
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2958
78.5%
Space Separator 522
 
13.8%
Other Punctuation 58
 
1.5%
Uppercase Letter 58
 
1.5%
Open Punctuation 58
 
1.5%
Final Punctuation 58
 
1.5%
Close Punctuation 58
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 348
11.8%
e 348
11.8%
r 290
9.8%
s 290
9.8%
u 232
 
7.8%
n 232
 
7.8%
t 174
 
5.9%
c 174
 
5.9%
m 174
 
5.9%
i 116
 
3.9%
Other values (7) 580
19.6%
Space Separator
ValueCountFrequency (%)
522
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 58
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3016
80.0%
Common 754
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 348
11.5%
e 348
11.5%
r 290
9.6%
s 290
9.6%
u 232
 
7.7%
n 232
 
7.7%
t 174
 
5.8%
c 174
 
5.8%
m 174
 
5.8%
i 116
 
3.8%
Other values (8) 638
21.2%
Common
ValueCountFrequency (%)
522
69.2%
, 58
 
7.7%
( 58
 
7.7%
’ 58
 
7.7%
) 58
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3596
95.4%
None 116
 
3.1%
Punctuation 58
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
522
14.5%
a 348
9.7%
e 348
9.7%
r 290
 
8.1%
s 290
 
8.1%
u 232
 
6.5%
n 232
 
6.5%
t 174
 
4.8%
c 174
 
4.8%
m 174
 
4.8%
Other values (10) 812
22.6%
None
ValueCountFrequency (%)
é 58
50.0%
ê 58
50.0%
Punctuation
ValueCountFrequency (%)
’ 58
100.0%

securité_dans_espace_public_q14_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1159
Missing (%)80.0%
Memory size103.8 KiB
Mauvais service dans un commerce (magasin, restaurant ou café)
289 

Length

Max length62
Median length62
Mean length62
Min length62

Characters and Unicode

Total characters17918
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMauvais service dans un commerce (magasin, restaurant ou café)
2nd rowMauvais service dans un commerce (magasin, restaurant ou café)
3rd rowMauvais service dans un commerce (magasin, restaurant ou café)
4th rowMauvais service dans un commerce (magasin, restaurant ou café)
5th rowMauvais service dans un commerce (magasin, restaurant ou café)

Common Values

ValueCountFrequency (%)
Mauvais service dans un commerce (magasin, restaurant ou café) 289
 
20.0%
(Missing) 1159
80.0%

Length

2023-06-18T04:18:39.293031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:39.714234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
mauvais 289
11.1%
service 289
11.1%
dans 289
11.1%
un 289
11.1%
commerce 289
11.1%
magasin 289
11.1%
restaurant 289
11.1%
ou 289
11.1%
café 289
11.1%

Most occurring characters

ValueCountFrequency (%)
2312
12.9%
a 2312
12.9%
s 1445
 
8.1%
e 1445
 
8.1%
u 1156
 
6.5%
r 1156
 
6.5%
c 1156
 
6.5%
n 1156
 
6.5%
i 867
 
4.8%
m 867
 
4.8%
Other values (11) 4046
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14450
80.6%
Space Separator 2312
 
12.9%
Uppercase Letter 289
 
1.6%
Other Punctuation 289
 
1.6%
Open Punctuation 289
 
1.6%
Close Punctuation 289
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2312
16.0%
s 1445
10.0%
e 1445
10.0%
u 1156
8.0%
r 1156
8.0%
c 1156
8.0%
n 1156
8.0%
i 867
 
6.0%
m 867
 
6.0%
t 578
 
4.0%
Other values (6) 2312
16.0%
Space Separator
ValueCountFrequency (%)
2312
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 289
100.0%
Other Punctuation
ValueCountFrequency (%)
, 289
100.0%
Open Punctuation
ValueCountFrequency (%)
( 289
100.0%
Close Punctuation
ValueCountFrequency (%)
) 289
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14739
82.3%
Common 3179
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2312
15.7%
s 1445
9.8%
e 1445
9.8%
u 1156
7.8%
r 1156
7.8%
c 1156
7.8%
n 1156
7.8%
i 867
 
5.9%
m 867
 
5.9%
t 578
 
3.9%
Other values (7) 2601
17.6%
Common
ValueCountFrequency (%)
2312
72.7%
, 289
 
9.1%
( 289
 
9.1%
) 289
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17629
98.4%
None 289
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2312
13.1%
a 2312
13.1%
s 1445
 
8.2%
e 1445
 
8.2%
u 1156
 
6.6%
r 1156
 
6.6%
c 1156
 
6.6%
n 1156
 
6.6%
i 867
 
4.9%
m 867
 
4.9%
Other values (10) 3757
21.3%
None
ValueCountFrequency (%)
é 289
100.0%

securité_dans_espace_public_q14_9
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing692
Missing (%)47.8%
Memory size81.1 KiB
Regard insistant
756 

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters12096
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRegard insistant
2nd rowRegard insistant
3rd rowRegard insistant
4th rowRegard insistant
5th rowRegard insistant

Common Values

ValueCountFrequency (%)
Regard insistant 756
52.2%
(Missing) 692
47.8%

Length

2023-06-18T04:18:39.907351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:40.367929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
regard 756
50.0%
insistant 756
50.0%

Most occurring characters

ValueCountFrequency (%)
a 1512
12.5%
i 1512
12.5%
n 1512
12.5%
s 1512
12.5%
t 1512
12.5%
R 756
6.2%
e 756
6.2%
g 756
6.2%
r 756
6.2%
d 756
6.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10584
87.5%
Uppercase Letter 756
 
6.2%
Space Separator 756
 
6.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1512
14.3%
i 1512
14.3%
n 1512
14.3%
s 1512
14.3%
t 1512
14.3%
e 756
7.1%
g 756
7.1%
r 756
7.1%
d 756
7.1%
Uppercase Letter
ValueCountFrequency (%)
R 756
100.0%
Space Separator
ValueCountFrequency (%)
756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11340
93.8%
Common 756
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1512
13.3%
i 1512
13.3%
n 1512
13.3%
s 1512
13.3%
t 1512
13.3%
R 756
6.7%
e 756
6.7%
g 756
6.7%
r 756
6.7%
d 756
6.7%
Common
ValueCountFrequency (%)
756
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12096
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1512
12.5%
i 1512
12.5%
n 1512
12.5%
s 1512
12.5%
t 1512
12.5%
R 756
6.2%
e 756
6.2%
g 756
6.2%
r 756
6.2%
d 756
6.2%

securité_dans_espace_public_q14_10
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.0%
Missing1349
Missing (%)93.2%
Memory size58.8 KiB
Autre
99 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters495
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAutre
2nd rowAutre
3rd rowAutre
4th rowAutre
5th rowAutre

Common Values

ValueCountFrequency (%)
Autre 99
 
6.8%
(Missing) 1349
93.2%

Length

2023-06-18T04:18:40.811848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:41.025293image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
autre 99
100.0%

Most occurring characters

ValueCountFrequency (%)
A 99
20.0%
u 99
20.0%
t 99
20.0%
r 99
20.0%
e 99
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 396
80.0%
Uppercase Letter 99
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 99
25.0%
t 99
25.0%
r 99
25.0%
e 99
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 99
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 495
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 99
20.0%
u 99
20.0%
t 99
20.0%
r 99
20.0%
e 99
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 99
20.0%
u 99
20.0%
t 99
20.0%
r 99
20.0%
e 99
20.0%

securité_dans_espace_public_q14_11
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1081
Missing (%)74.7%
Memory size147.7 KiB
Rien de tout cela ne m’est arrivé dans les vingt quatre derniers mois
367 

Length

Max length69
Median length69
Mean length69
Min length69

Characters and Unicode

Total characters25323
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRien de tout cela ne m’est arrivé dans les vingt quatre derniers mois
2nd rowRien de tout cela ne m’est arrivé dans les vingt quatre derniers mois
3rd rowRien de tout cela ne m’est arrivé dans les vingt quatre derniers mois
4th rowRien de tout cela ne m’est arrivé dans les vingt quatre derniers mois
5th rowRien de tout cela ne m’est arrivé dans les vingt quatre derniers mois

Common Values

ValueCountFrequency (%)
Rien de tout cela ne m’est arrivé dans les vingt quatre derniers mois 367
 
25.3%
(Missing) 1081
74.7%

Length

2023-06-18T04:18:41.205466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:41.445427image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
rien 367
 
7.7%
de 367
 
7.7%
tout 367
 
7.7%
cela 367
 
7.7%
ne 367
 
7.7%
m’est 367
 
7.7%
arrivé 367
 
7.7%
dans 367
 
7.7%
les 367
 
7.7%
vingt 367
 
7.7%
Other values (3) 1101
23.1%

Most occurring characters

ValueCountFrequency (%)
4037
15.9%
e 3303
13.0%
n 1835
 
7.2%
t 1835
 
7.2%
r 1835
 
7.2%
s 1835
 
7.2%
i 1835
 
7.2%
a 1468
 
5.8%
d 1101
 
4.3%
l 734
 
2.9%
Other values (11) 5505
21.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20185
79.7%
Space Separator 4404
 
17.4%
Uppercase Letter 367
 
1.4%
Final Punctuation 367
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3303
16.4%
n 1835
9.1%
t 1835
9.1%
r 1835
9.1%
s 1835
9.1%
i 1835
9.1%
a 1468
 
7.3%
d 1101
 
5.5%
l 734
 
3.6%
m 734
 
3.6%
Other values (7) 3670
18.2%
Space Separator
ValueCountFrequency (%)
4037
91.7%
  367
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
R 367
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 367
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20552
81.2%
Common 4771
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3303
16.1%
n 1835
8.9%
t 1835
8.9%
r 1835
8.9%
s 1835
8.9%
i 1835
8.9%
a 1468
 
7.1%
d 1101
 
5.4%
l 734
 
3.6%
m 734
 
3.6%
Other values (8) 4037
19.6%
Common
ValueCountFrequency (%)
4037
84.6%
  367
 
7.7%
’ 367
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24222
95.7%
None 734
 
2.9%
Punctuation 367
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4037
16.7%
e 3303
13.6%
n 1835
7.6%
t 1835
7.6%
r 1835
7.6%
s 1835
7.6%
i 1835
7.6%
a 1468
 
6.1%
d 1101
 
4.5%
l 734
 
3.0%
Other values (8) 4404
18.2%
None
ValueCountFrequency (%)
  367
50.0%
é 367
50.0%
Punctuation
ValueCountFrequency (%)
’ 367
100.0%

securité_dans_espace_public_q15_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing831
Missing (%)57.4%
Memory size78.4 KiB
Transport en commun
617 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11723
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTransport en commun
2nd rowTransport en commun
3rd rowTransport en commun
4th rowTransport en commun
5th rowTransport en commun

Common Values

ValueCountFrequency (%)
Transport en commun 617
42.6%
(Missing) 831
57.4%

Length

2023-06-18T04:18:41.653595image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:41.889465image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
transport 617
33.3%
en 617
33.3%
commun 617
33.3%

Most occurring characters

ValueCountFrequency (%)
n 1851
15.8%
r 1234
10.5%
o 1234
10.5%
1234
10.5%
m 1234
10.5%
T 617
 
5.3%
a 617
 
5.3%
s 617
 
5.3%
p 617
 
5.3%
t 617
 
5.3%
Other values (3) 1851
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9872
84.2%
Space Separator 1234
 
10.5%
Uppercase Letter 617
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1851
18.8%
r 1234
12.5%
o 1234
12.5%
m 1234
12.5%
a 617
 
6.2%
s 617
 
6.2%
p 617
 
6.2%
t 617
 
6.2%
e 617
 
6.2%
c 617
 
6.2%
Space Separator
ValueCountFrequency (%)
1234
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 617
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10489
89.5%
Common 1234
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1851
17.6%
r 1234
11.8%
o 1234
11.8%
m 1234
11.8%
T 617
 
5.9%
a 617
 
5.9%
s 617
 
5.9%
p 617
 
5.9%
t 617
 
5.9%
e 617
 
5.9%
Other values (2) 1234
11.8%
Common
ValueCountFrequency (%)
1234
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11723
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1851
15.8%
r 1234
10.5%
o 1234
10.5%
1234
10.5%
m 1234
10.5%
T 617
 
5.3%
a 617
 
5.3%
s 617
 
5.3%
p 617
 
5.3%
t 617
 
5.3%
Other values (3) 1851
15.8%

securité_dans_espace_public_q15_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.5%
Missing1380
Missing (%)95.3%
Memory size58.7 KiB
Piste cyclable
68 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters952
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPiste cyclable
2nd rowPiste cyclable
3rd rowPiste cyclable
4th rowPiste cyclable
5th rowPiste cyclable

Common Values

ValueCountFrequency (%)
Piste cyclable 68
 
4.7%
(Missing) 1380
95.3%

Length

2023-06-18T04:18:42.082030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:42.310592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
piste 68
50.0%
cyclable 68
50.0%

Most occurring characters

ValueCountFrequency (%)
e 136
14.3%
c 136
14.3%
l 136
14.3%
P 68
7.1%
i 68
7.1%
s 68
7.1%
t 68
7.1%
68
7.1%
y 68
7.1%
a 68
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 816
85.7%
Uppercase Letter 68
 
7.1%
Space Separator 68
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 136
16.7%
c 136
16.7%
l 136
16.7%
i 68
8.3%
s 68
8.3%
t 68
8.3%
y 68
8.3%
a 68
8.3%
b 68
8.3%
Uppercase Letter
ValueCountFrequency (%)
P 68
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 884
92.9%
Common 68
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 136
15.4%
c 136
15.4%
l 136
15.4%
P 68
7.7%
i 68
7.7%
s 68
7.7%
t 68
7.7%
y 68
7.7%
a 68
7.7%
b 68
7.7%
Common
ValueCountFrequency (%)
68
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 952
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 136
14.3%
c 136
14.3%
l 136
14.3%
P 68
7.1%
i 68
7.1%
s 68
7.1%
t 68
7.1%
68
7.1%
y 68
7.1%
a 68
7.1%

securité_dans_espace_public_q15_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)2.7%
Missing1411
Missing (%)97.4%
Memory size61.6 KiB
Bibliothèque municipale ou Maison de la culture
37 

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters1739
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBibliothèque municipale ou Maison de la culture
2nd rowBibliothèque municipale ou Maison de la culture
3rd rowBibliothèque municipale ou Maison de la culture
4th rowBibliothèque municipale ou Maison de la culture
5th rowBibliothèque municipale ou Maison de la culture

Common Values

ValueCountFrequency (%)
Bibliothèque municipale ou Maison de la culture 37
 
2.6%
(Missing) 1411
97.4%

Length

2023-06-18T04:18:42.503474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:42.801149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
bibliothèque 37
14.3%
municipale 37
14.3%
ou 37
14.3%
maison 37
14.3%
de 37
14.3%
la 37
14.3%
culture 37
14.3%

Most occurring characters

ValueCountFrequency (%)
222
12.8%
u 185
10.6%
i 185
10.6%
e 148
 
8.5%
l 148
 
8.5%
o 111
 
6.4%
a 111
 
6.4%
c 74
 
4.3%
t 74
 
4.3%
n 74
 
4.3%
Other values (11) 407
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1443
83.0%
Space Separator 222
 
12.8%
Uppercase Letter 74
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 185
12.8%
i 185
12.8%
e 148
10.3%
l 148
10.3%
o 111
 
7.7%
a 111
 
7.7%
c 74
 
5.1%
t 74
 
5.1%
n 74
 
5.1%
d 37
 
2.6%
Other values (8) 296
20.5%
Uppercase Letter
ValueCountFrequency (%)
M 37
50.0%
B 37
50.0%
Space Separator
ValueCountFrequency (%)
222
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1517
87.2%
Common 222
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 185
12.2%
i 185
12.2%
e 148
 
9.8%
l 148
 
9.8%
o 111
 
7.3%
a 111
 
7.3%
c 74
 
4.9%
t 74
 
4.9%
n 74
 
4.9%
d 37
 
2.4%
Other values (10) 370
24.4%
Common
ValueCountFrequency (%)
222
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1702
97.9%
None 37
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
13.0%
u 185
10.9%
i 185
10.9%
e 148
 
8.7%
l 148
 
8.7%
o 111
 
6.5%
a 111
 
6.5%
c 74
 
4.3%
t 74
 
4.3%
n 74
 
4.3%
Other values (10) 370
21.7%
None
ValueCountFrequency (%)
è 37
100.0%

securité_dans_espace_public_q15_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing1319
Missing (%)91.1%
Memory size62.7 KiB
Centre sportif ou communautaire
129 

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters3999
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCentre sportif ou communautaire
2nd rowCentre sportif ou communautaire
3rd rowCentre sportif ou communautaire
4th rowCentre sportif ou communautaire
5th rowCentre sportif ou communautaire

Common Values

ValueCountFrequency (%)
Centre sportif ou communautaire 129
 
8.9%
(Missing) 1319
91.1%

Length

2023-06-18T04:18:43.249816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:43.580975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
centre 129
25.0%
sportif 129
25.0%
ou 129
25.0%
communautaire 129
25.0%

Most occurring characters

ValueCountFrequency (%)
e 387
9.7%
t 387
9.7%
r 387
9.7%
387
9.7%
o 387
9.7%
u 387
9.7%
n 258
 
6.5%
i 258
 
6.5%
m 258
 
6.5%
a 258
 
6.5%
Other values (5) 645
16.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3483
87.1%
Space Separator 387
 
9.7%
Uppercase Letter 129
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 387
11.1%
t 387
11.1%
r 387
11.1%
o 387
11.1%
u 387
11.1%
n 258
7.4%
i 258
7.4%
m 258
7.4%
a 258
7.4%
s 129
 
3.7%
Other values (3) 387
11.1%
Space Separator
ValueCountFrequency (%)
387
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3612
90.3%
Common 387
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 387
10.7%
t 387
10.7%
r 387
10.7%
o 387
10.7%
u 387
10.7%
n 258
7.1%
i 258
7.1%
m 258
7.1%
a 258
7.1%
C 129
 
3.6%
Other values (4) 516
14.3%
Common
ValueCountFrequency (%)
387
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3999
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 387
9.7%
t 387
9.7%
r 387
9.7%
387
9.7%
o 387
9.7%
u 387
9.7%
n 258
 
6.5%
i 258
 
6.5%
m 258
 
6.5%
a 258
 
6.5%
Other values (5) 645
16.1%

securité_dans_espace_public_q15_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1076
Missing (%)74.3%
Memory size86.8 KiB
Événement extérieur
372 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters7068
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÉvénement extérieur
2nd rowÉvénement extérieur
3rd rowÉvénement extérieur
4th rowÉvénement extérieur
5th rowÉvénement extérieur

Common Values

ValueCountFrequency (%)
Événement extérieur 372
 
25.7%
(Missing) 1076
74.3%

Length

2023-06-18T04:18:44.006634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:44.533970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
événement 372
50.0%
extérieur 372
50.0%

Most occurring characters

ValueCountFrequency (%)
e 1488
21.1%
é 744
10.5%
n 744
10.5%
t 744
10.5%
r 744
10.5%
É 372
 
5.3%
v 372
 
5.3%
m 372
 
5.3%
372
 
5.3%
x 372
 
5.3%
Other values (2) 744
10.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6324
89.5%
Uppercase Letter 372
 
5.3%
Space Separator 372
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1488
23.5%
é 744
11.8%
n 744
11.8%
t 744
11.8%
r 744
11.8%
v 372
 
5.9%
m 372
 
5.9%
x 372
 
5.9%
i 372
 
5.9%
u 372
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
É 372
100.0%
Space Separator
ValueCountFrequency (%)
372
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6696
94.7%
Common 372
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1488
22.2%
é 744
11.1%
n 744
11.1%
t 744
11.1%
r 744
11.1%
É 372
 
5.6%
v 372
 
5.6%
m 372
 
5.6%
x 372
 
5.6%
i 372
 
5.6%
Common
ValueCountFrequency (%)
372
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5952
84.2%
None 1116
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1488
25.0%
n 744
12.5%
t 744
12.5%
r 744
12.5%
v 372
 
6.2%
m 372
 
6.2%
372
 
6.2%
x 372
 
6.2%
i 372
 
6.2%
u 372
 
6.2%
None
ValueCountFrequency (%)
é 744
66.7%
É 372
33.3%

securité_dans_espace_public_q15_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing735
Missing (%)50.8%
Memory size77.6 KiB
Rue ou ruelle
713 

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters9269
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRue ou ruelle
2nd rowRue ou ruelle
3rd rowRue ou ruelle
4th rowRue ou ruelle
5th rowRue ou ruelle

Common Values

ValueCountFrequency (%)
Rue ou ruelle 713
49.2%
(Missing) 735
50.8%

Length

2023-06-18T04:18:44.941747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:45.424326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
rue 713
33.3%
ou 713
33.3%
ruelle 713
33.3%

Most occurring characters

ValueCountFrequency (%)
u 2139
23.1%
e 2139
23.1%
1426
15.4%
l 1426
15.4%
R 713
 
7.7%
o 713
 
7.7%
r 713
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7130
76.9%
Space Separator 1426
 
15.4%
Uppercase Letter 713
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 2139
30.0%
e 2139
30.0%
l 1426
20.0%
o 713
 
10.0%
r 713
 
10.0%
Space Separator
ValueCountFrequency (%)
1426
100.0%
Uppercase Letter
ValueCountFrequency (%)
R 713
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7843
84.6%
Common 1426
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 2139
27.3%
e 2139
27.3%
l 1426
18.2%
R 713
 
9.1%
o 713
 
9.1%
r 713
 
9.1%
Common
ValueCountFrequency (%)
1426
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 2139
23.1%
e 2139
23.1%
1426
15.4%
l 1426
15.4%
R 713
 
7.7%
o 713
 
7.7%
r 713
 
7.7%

securité_dans_espace_public_q15_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1172
Missing (%)80.9%
Memory size68.0 KiB
Parc ou terrain de sports
276 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters6900
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowParc ou terrain de sports
2nd rowParc ou terrain de sports
3rd rowParc ou terrain de sports
4th rowParc ou terrain de sports
5th rowParc ou terrain de sports

Common Values

ValueCountFrequency (%)
Parc ou terrain de sports 276
 
19.1%
(Missing) 1172
80.9%

Length

2023-06-18T04:18:45.830948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:46.258611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
parc 276
20.0%
ou 276
20.0%
terrain 276
20.0%
de 276
20.0%
sports 276
20.0%

Most occurring characters

ValueCountFrequency (%)
r 1104
16.0%
1104
16.0%
a 552
8.0%
o 552
8.0%
t 552
8.0%
e 552
8.0%
s 552
8.0%
P 276
 
4.0%
c 276
 
4.0%
u 276
 
4.0%
Other values (4) 1104
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5520
80.0%
Space Separator 1104
 
16.0%
Uppercase Letter 276
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 1104
20.0%
a 552
10.0%
o 552
10.0%
t 552
10.0%
e 552
10.0%
s 552
10.0%
c 276
 
5.0%
u 276
 
5.0%
i 276
 
5.0%
n 276
 
5.0%
Other values (2) 552
10.0%
Space Separator
ValueCountFrequency (%)
1104
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5796
84.0%
Common 1104
 
16.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 1104
19.0%
a 552
9.5%
o 552
9.5%
t 552
9.5%
e 552
9.5%
s 552
9.5%
P 276
 
4.8%
c 276
 
4.8%
u 276
 
4.8%
i 276
 
4.8%
Other values (3) 828
14.3%
Common
ValueCountFrequency (%)
1104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 1104
16.0%
1104
16.0%
a 552
8.0%
o 552
8.0%
t 552
8.0%
e 552
8.0%
s 552
8.0%
P 276
 
4.0%
c 276
 
4.0%
u 276
 
4.0%
Other values (4) 1104
16.0%

securité_dans_espace_public_q15_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1100
Missing (%)76.0%
Memory size65.2 KiB
Commerce
348 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters2784
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCommerce
2nd rowCommerce
3rd rowCommerce
4th rowCommerce
5th rowCommerce

Common Values

ValueCountFrequency (%)
Commerce 348
 
24.0%
(Missing) 1100
76.0%

Length

2023-06-18T04:18:46.630892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:47.073225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
commerce 348
100.0%

Most occurring characters

ValueCountFrequency (%)
m 696
25.0%
e 696
25.0%
C 348
12.5%
o 348
12.5%
r 348
12.5%
c 348
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2436
87.5%
Uppercase Letter 348
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 696
28.6%
e 696
28.6%
o 348
14.3%
r 348
14.3%
c 348
14.3%
Uppercase Letter
ValueCountFrequency (%)
C 348
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2784
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 696
25.0%
e 696
25.0%
C 348
12.5%
o 348
12.5%
r 348
12.5%
c 348
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2784
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 696
25.0%
e 696
25.0%
C 348
12.5%
o 348
12.5%
r 348
12.5%
c 348
12.5%

securité_dans_espace_public_q15_9
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1139
Missing (%)78.7%
Memory size75.7 KiB
Sur l'internet (ex.: Facebook, courriels, etc)
309 

Length

Max length46
Median length46
Mean length46
Min length46

Characters and Unicode

Total characters14214
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSur l'internet (ex.: Facebook, courriels, etc)
2nd rowSur l'internet (ex.: Facebook, courriels, etc)
3rd rowSur l'internet (ex.: Facebook, courriels, etc)
4th rowSur l'internet (ex.: Facebook, courriels, etc)
5th rowSur l'internet (ex.: Facebook, courriels, etc)

Common Values

ValueCountFrequency (%)
Sur l'internet (ex.: Facebook, courriels, etc) 309
 
21.3%
(Missing) 1139
78.7%

Length

2023-06-18T04:18:47.463714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:47.905996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
sur 309
16.7%
l'internet 309
16.7%
ex 309
16.7%
facebook 309
16.7%
courriels 309
16.7%
etc 309
16.7%

Most occurring characters

ValueCountFrequency (%)
e 1854
13.0%
1545
 
10.9%
r 1236
 
8.7%
c 927
 
6.5%
t 927
 
6.5%
o 927
 
6.5%
l 618
 
4.3%
i 618
 
4.3%
n 618
 
4.3%
, 618
 
4.3%
Other values (13) 4326
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9888
69.6%
Space Separator 1545
 
10.9%
Other Punctuation 1545
 
10.9%
Uppercase Letter 618
 
4.3%
Open Punctuation 309
 
2.2%
Close Punctuation 309
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1854
18.8%
r 1236
12.5%
c 927
9.4%
t 927
9.4%
o 927
9.4%
l 618
 
6.2%
i 618
 
6.2%
n 618
 
6.2%
u 618
 
6.2%
s 309
 
3.1%
Other values (4) 1236
12.5%
Other Punctuation
ValueCountFrequency (%)
, 618
40.0%
: 309
20.0%
. 309
20.0%
' 309
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 309
50.0%
F 309
50.0%
Space Separator
ValueCountFrequency (%)
1545
100.0%
Open Punctuation
ValueCountFrequency (%)
( 309
100.0%
Close Punctuation
ValueCountFrequency (%)
) 309
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10506
73.9%
Common 3708
 
26.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1854
17.6%
r 1236
11.8%
c 927
8.8%
t 927
8.8%
o 927
8.8%
l 618
 
5.9%
i 618
 
5.9%
n 618
 
5.9%
u 618
 
5.9%
S 309
 
2.9%
Other values (6) 1854
17.6%
Common
ValueCountFrequency (%)
1545
41.7%
, 618
 
16.7%
: 309
 
8.3%
. 309
 
8.3%
( 309
 
8.3%
' 309
 
8.3%
) 309
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14214
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1854
13.0%
1545
 
10.9%
r 1236
 
8.7%
c 927
 
6.5%
t 927
 
6.5%
o 927
 
6.5%
l 618
 
4.3%
i 618
 
4.3%
n 618
 
4.3%
, 618
 
4.3%
Other values (13) 4326
30.4%

securité_dans_espace_public_q16
Categorical

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct3
Distinct (%)0.3%
Missing365
Missing (%)25.2%
Memory size84.3 KiB
Non
936 
Je préfère ne pas répondre
 
86
Oui
 
61

Length

Max length26
Median length3
Mean length4.8264081
Min length3

Characters and Unicode

Total characters5227
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowOui
3rd rowNon
4th rowNon
5th rowJe préfère ne pas répondre

Common Values

ValueCountFrequency (%)
Non 936
64.6%
Je préfère ne pas répondre 86
 
5.9%
Oui 61
 
4.2%
(Missing) 365
 
25.2%

Length

2023-06-18T04:18:48.341366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:48.698970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 936
65.6%
je 86
 
6.0%
préfère 86
 
6.0%
ne 86
 
6.0%
pas 86
 
6.0%
répondre 86
 
6.0%
oui 61
 
4.3%

Most occurring characters

ValueCountFrequency (%)
n 1108
21.2%
o 1022
19.6%
N 936
17.9%
r 344
 
6.6%
e 344
 
6.6%
344
 
6.6%
p 258
 
4.9%
é 172
 
3.3%
J 86
 
1.6%
f 86
 
1.6%
Other values (7) 527
10.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3800
72.7%
Uppercase Letter 1083
 
20.7%
Space Separator 344
 
6.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1108
29.2%
o 1022
26.9%
r 344
 
9.1%
e 344
 
9.1%
p 258
 
6.8%
é 172
 
4.5%
f 86
 
2.3%
è 86
 
2.3%
a 86
 
2.3%
s 86
 
2.3%
Other values (3) 208
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
N 936
86.4%
J 86
 
7.9%
O 61
 
5.6%
Space Separator
ValueCountFrequency (%)
344
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4883
93.4%
Common 344
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1108
22.7%
o 1022
20.9%
N 936
19.2%
r 344
 
7.0%
e 344
 
7.0%
p 258
 
5.3%
é 172
 
3.5%
J 86
 
1.8%
f 86
 
1.8%
è 86
 
1.8%
Other values (6) 441
 
9.0%
Common
ValueCountFrequency (%)
344
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4969
95.1%
None 258
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1108
22.3%
o 1022
20.6%
N 936
18.8%
r 344
 
6.9%
e 344
 
6.9%
344
 
6.9%
p 258
 
5.2%
J 86
 
1.7%
f 86
 
1.7%
a 86
 
1.7%
Other values (5) 355
 
7.1%
None
ValueCountFrequency (%)
é 172
66.7%
è 86
33.3%

securité_dans_espace_public_q17_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing1009
Missing (%)69.7%
Memory size130.0 KiB
Ce n’était pas un acte réprimé par la loi
439 

Length

Max length41
Median length41
Mean length41
Min length41

Characters and Unicode

Total characters17999
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCe n’était pas un acte réprimé par la loi
2nd rowCe n’était pas un acte réprimé par la loi
3rd rowCe n’était pas un acte réprimé par la loi
4th rowCe n’était pas un acte réprimé par la loi
5th rowCe n’était pas un acte réprimé par la loi

Common Values

ValueCountFrequency (%)
Ce n’était pas un acte réprimé par la loi 439
30.3%
(Missing) 1009
69.7%

Length

2023-06-18T04:18:48.923648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:49.160164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ce 439
11.1%
n’était 439
11.1%
pas 439
11.1%
un 439
11.1%
acte 439
11.1%
réprimé 439
11.1%
par 439
11.1%
la 439
11.1%
loi 439
11.1%

Most occurring characters

ValueCountFrequency (%)
3512
19.5%
a 2195
12.2%
i 1317
 
7.3%
é 1317
 
7.3%
t 1317
 
7.3%
p 1317
 
7.3%
r 1317
 
7.3%
n 878
 
4.9%
l 878
 
4.9%
e 878
 
4.9%
Other values (7) 3073
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13609
75.6%
Space Separator 3512
 
19.5%
Uppercase Letter 439
 
2.4%
Final Punctuation 439
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2195
16.1%
i 1317
9.7%
é 1317
9.7%
t 1317
9.7%
p 1317
9.7%
r 1317
9.7%
n 878
 
6.5%
l 878
 
6.5%
e 878
 
6.5%
c 439
 
3.2%
Other values (4) 1756
12.9%
Space Separator
ValueCountFrequency (%)
3512
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 439
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 439
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14048
78.0%
Common 3951
 
22.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2195
15.6%
i 1317
9.4%
é 1317
9.4%
t 1317
9.4%
p 1317
9.4%
r 1317
9.4%
n 878
 
6.2%
l 878
 
6.2%
e 878
 
6.2%
c 439
 
3.1%
Other values (5) 2195
15.6%
Common
ValueCountFrequency (%)
3512
88.9%
’ 439
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16243
90.2%
None 1317
 
7.3%
Punctuation 439
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3512
21.6%
a 2195
13.5%
i 1317
 
8.1%
t 1317
 
8.1%
p 1317
 
8.1%
r 1317
 
8.1%
n 878
 
5.4%
l 878
 
5.4%
e 878
 
5.4%
c 439
 
2.7%
Other values (5) 2195
13.5%
None
ValueCountFrequency (%)
é 1317
100.0%
Punctuation
ValueCountFrequency (%)
’ 439
100.0%

securité_dans_espace_public_q17_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing979
Missing (%)67.6%
Memory size135.5 KiB
J’ai pensé que c’était un acte trop banal
469 

Length

Max length41
Median length41
Mean length41
Min length41

Characters and Unicode

Total characters19229
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ’ai pensé que c’était un acte trop banal
2nd rowJ’ai pensé que c’était un acte trop banal
3rd rowJ’ai pensé que c’était un acte trop banal
4th rowJ’ai pensé que c’était un acte trop banal
5th rowJ’ai pensé que c’était un acte trop banal

Common Values

ValueCountFrequency (%)
J’ai pensé que c’était un acte trop banal 469
32.4%
(Missing) 979
67.6%

Length

2023-06-18T04:18:49.358375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:49.568443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
j’ai 469
12.5%
pensé 469
12.5%
que 469
12.5%
c’était 469
12.5%
un 469
12.5%
acte 469
12.5%
trop 469
12.5%
banal 469
12.5%

Most occurring characters

ValueCountFrequency (%)
3283
17.1%
a 2345
12.2%
t 1876
9.8%
e 1407
 
7.3%
n 1407
 
7.3%
é 938
 
4.9%
i 938
 
4.9%
p 938
 
4.9%
’ 938
 
4.9%
u 938
 
4.9%
Other values (8) 4221
22.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14539
75.6%
Space Separator 3283
 
17.1%
Final Punctuation 938
 
4.9%
Uppercase Letter 469
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2345
16.1%
t 1876
12.9%
e 1407
9.7%
n 1407
9.7%
é 938
 
6.5%
i 938
 
6.5%
p 938
 
6.5%
u 938
 
6.5%
c 938
 
6.5%
r 469
 
3.2%
Other values (5) 2345
16.1%
Space Separator
ValueCountFrequency (%)
3283
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 938
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 469
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15008
78.0%
Common 4221
 
22.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2345
15.6%
t 1876
12.5%
e 1407
9.4%
n 1407
9.4%
é 938
 
6.2%
i 938
 
6.2%
p 938
 
6.2%
u 938
 
6.2%
c 938
 
6.2%
r 469
 
3.1%
Other values (6) 2814
18.8%
Common
ValueCountFrequency (%)
3283
77.8%
’ 938
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17353
90.2%
None 938
 
4.9%
Punctuation 938
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3283
18.9%
a 2345
13.5%
t 1876
10.8%
e 1407
8.1%
n 1407
8.1%
i 938
 
5.4%
p 938
 
5.4%
u 938
 
5.4%
c 938
 
5.4%
r 469
 
2.7%
Other values (6) 2814
16.2%
None
ValueCountFrequency (%)
é 938
100.0%
Punctuation
ValueCountFrequency (%)
’ 938
100.0%

securité_dans_espace_public_q17_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing1321
Missing (%)91.2%
Memory size73.2 KiB
J’ai eu peur des représailles
127 

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters3683
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ’ai eu peur des représailles
2nd rowJ’ai eu peur des représailles
3rd rowJ’ai eu peur des représailles
4th rowJ’ai eu peur des représailles
5th rowJ’ai eu peur des représailles

Common Values

ValueCountFrequency (%)
J’ai eu peur des représailles 127
 
8.8%
(Missing) 1321
91.2%

Length

2023-06-18T04:18:50.387391image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:50.612009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
j’ai 127
20.0%
eu 127
20.0%
peur 127
20.0%
des 127
20.0%
représailles 127
20.0%

Most occurring characters

ValueCountFrequency (%)
e 635
17.2%
508
13.8%
r 381
10.3%
s 381
10.3%
a 254
 
6.9%
i 254
 
6.9%
u 254
 
6.9%
p 254
 
6.9%
l 254
 
6.9%
J 127
 
3.4%
Other values (3) 381
10.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2921
79.3%
Space Separator 508
 
13.8%
Uppercase Letter 127
 
3.4%
Final Punctuation 127
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 635
21.7%
r 381
13.0%
s 381
13.0%
a 254
 
8.7%
i 254
 
8.7%
u 254
 
8.7%
p 254
 
8.7%
l 254
 
8.7%
d 127
 
4.3%
é 127
 
4.3%
Space Separator
ValueCountFrequency (%)
508
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 127
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3048
82.8%
Common 635
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 635
20.8%
r 381
12.5%
s 381
12.5%
a 254
 
8.3%
i 254
 
8.3%
u 254
 
8.3%
p 254
 
8.3%
l 254
 
8.3%
J 127
 
4.2%
d 127
 
4.2%
Common
ValueCountFrequency (%)
508
80.0%
’ 127
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3429
93.1%
Punctuation 127
 
3.4%
None 127
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 635
18.5%
508
14.8%
r 381
11.1%
s 381
11.1%
a 254
 
7.4%
i 254
 
7.4%
u 254
 
7.4%
p 254
 
7.4%
l 254
 
7.4%
J 127
 
3.7%
Punctuation
ValueCountFrequency (%)
’ 127
100.0%
None
ValueCountFrequency (%)
é 127
100.0%

securité_dans_espace_public_q17_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.4%
Missing1206
Missing (%)83.3%
Memory size84.3 KiB
Je ne savais pas à qui porter plainte
242 

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters8954
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe ne savais pas à qui porter plainte
2nd rowJe ne savais pas à qui porter plainte
3rd rowJe ne savais pas à qui porter plainte
4th rowJe ne savais pas à qui porter plainte
5th rowJe ne savais pas à qui porter plainte

Common Values

ValueCountFrequency (%)
Je ne savais pas à qui porter plainte 242
 
16.7%
(Missing) 1206
83.3%

Length

2023-06-18T04:18:50.799307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:51.048535image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
je 242
12.5%
ne 242
12.5%
savais 242
12.5%
pas 242
12.5%
à 242
12.5%
qui 242
12.5%
porter 242
12.5%
plainte 242
12.5%

Most occurring characters

ValueCountFrequency (%)
1694
18.9%
e 968
10.8%
a 968
10.8%
s 726
8.1%
i 726
8.1%
p 726
8.1%
n 484
 
5.4%
r 484
 
5.4%
t 484
 
5.4%
J 242
 
2.7%
Other values (6) 1452
16.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7018
78.4%
Space Separator 1694
 
18.9%
Uppercase Letter 242
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 968
13.8%
a 968
13.8%
s 726
10.3%
i 726
10.3%
p 726
10.3%
n 484
6.9%
r 484
6.9%
t 484
6.9%
v 242
 
3.4%
à 242
 
3.4%
Other values (4) 968
13.8%
Space Separator
ValueCountFrequency (%)
1694
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7260
81.1%
Common 1694
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 968
13.3%
a 968
13.3%
s 726
10.0%
i 726
10.0%
p 726
10.0%
n 484
 
6.7%
r 484
 
6.7%
t 484
 
6.7%
J 242
 
3.3%
v 242
 
3.3%
Other values (5) 1210
16.7%
Common
ValueCountFrequency (%)
1694
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8712
97.3%
None 242
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1694
19.4%
e 968
11.1%
a 968
11.1%
s 726
8.3%
i 726
8.3%
p 726
8.3%
n 484
 
5.6%
r 484
 
5.6%
t 484
 
5.6%
J 242
 
2.8%
Other values (5) 1210
13.9%
None
ValueCountFrequency (%)
à 242
100.0%

securité_dans_espace_public_q17_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.8%
Missing1328
Missing (%)91.7%
Memory size62.8 KiB
Je ne voulais pas revivre le moment
120 

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters4200
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe ne voulais pas revivre le moment
2nd rowJe ne voulais pas revivre le moment
3rd rowJe ne voulais pas revivre le moment
4th rowJe ne voulais pas revivre le moment
5th rowJe ne voulais pas revivre le moment

Common Values

ValueCountFrequency (%)
Je ne voulais pas revivre le moment 120
 
8.3%
(Missing) 1328
91.7%

Length

2023-06-18T04:18:51.233782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:51.457886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
je 120
14.3%
ne 120
14.3%
voulais 120
14.3%
pas 120
14.3%
revivre 120
14.3%
le 120
14.3%
moment 120
14.3%

Most occurring characters

ValueCountFrequency (%)
e 720
17.1%
720
17.1%
v 360
8.6%
n 240
 
5.7%
o 240
 
5.7%
l 240
 
5.7%
a 240
 
5.7%
i 240
 
5.7%
s 240
 
5.7%
r 240
 
5.7%
Other values (5) 720
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3360
80.0%
Space Separator 720
 
17.1%
Uppercase Letter 120
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 720
21.4%
v 360
10.7%
n 240
 
7.1%
o 240
 
7.1%
l 240
 
7.1%
a 240
 
7.1%
i 240
 
7.1%
s 240
 
7.1%
r 240
 
7.1%
m 240
 
7.1%
Other values (3) 360
10.7%
Space Separator
ValueCountFrequency (%)
720
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3480
82.9%
Common 720
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 720
20.7%
v 360
10.3%
n 240
 
6.9%
o 240
 
6.9%
l 240
 
6.9%
a 240
 
6.9%
i 240
 
6.9%
s 240
 
6.9%
r 240
 
6.9%
m 240
 
6.9%
Other values (4) 480
13.8%
Common
ValueCountFrequency (%)
720
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4200
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 720
17.1%
720
17.1%
v 360
8.6%
n 240
 
5.7%
o 240
 
5.7%
l 240
 
5.7%
a 240
 
5.7%
i 240
 
5.7%
s 240
 
5.7%
r 240
 
5.7%
Other values (5) 720
17.1%

securité_dans_espace_public_q17_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)1.3%
Missing1370
Missing (%)94.6%
Memory size67.2 KiB
Je ne voulais pas devoir faire mon «coming out»
78 

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters3666
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe ne voulais pas devoir faire mon «coming out»
2nd rowJe ne voulais pas devoir faire mon «coming out»
3rd rowJe ne voulais pas devoir faire mon «coming out»
4th rowJe ne voulais pas devoir faire mon «coming out»
5th rowJe ne voulais pas devoir faire mon «coming out»

Common Values

ValueCountFrequency (%)
Je ne voulais pas devoir faire mon «coming out» 78
 
5.4%
(Missing) 1370
94.6%

Length

2023-06-18T04:18:51.639414image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:51.891240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
je 78
11.1%
ne 78
11.1%
voulais 78
11.1%
pas 78
11.1%
devoir 78
11.1%
faire 78
11.1%
mon 78
11.1%
«coming 78
11.1%
out» 78
11.1%

Most occurring characters

ValueCountFrequency (%)
624
17.0%
o 390
10.6%
i 312
 
8.5%
e 312
 
8.5%
n 234
 
6.4%
a 234
 
6.4%
s 156
 
4.3%
m 156
 
4.3%
v 156
 
4.3%
u 156
 
4.3%
Other values (11) 936
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2808
76.6%
Space Separator 624
 
17.0%
Initial Punctuation 78
 
2.1%
Uppercase Letter 78
 
2.1%
Final Punctuation 78
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 390
13.9%
i 312
11.1%
e 312
11.1%
n 234
8.3%
a 234
8.3%
s 156
 
5.6%
m 156
 
5.6%
v 156
 
5.6%
u 156
 
5.6%
r 156
 
5.6%
Other values (7) 546
19.4%
Space Separator
ValueCountFrequency (%)
624
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 78
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 78
100.0%
Final Punctuation
ValueCountFrequency (%)
» 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2886
78.7%
Common 780
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 390
13.5%
i 312
10.8%
e 312
10.8%
n 234
 
8.1%
a 234
 
8.1%
s 156
 
5.4%
m 156
 
5.4%
v 156
 
5.4%
u 156
 
5.4%
r 156
 
5.4%
Other values (8) 624
21.6%
Common
ValueCountFrequency (%)
624
80.0%
« 78
 
10.0%
» 78
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3510
95.7%
None 156
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
624
17.8%
o 390
11.1%
i 312
 
8.9%
e 312
 
8.9%
n 234
 
6.7%
a 234
 
6.7%
s 156
 
4.4%
m 156
 
4.4%
v 156
 
4.4%
u 156
 
4.4%
Other values (9) 780
22.2%
None
ValueCountFrequency (%)
« 78
50.0%
» 78
50.0%

securité_dans_espace_public_q17_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing913
Missing (%)63.1%
Memory size135.6 KiB
J’ai pensé que ce serait sans effet
535 

Length

Max length35
Median length35
Mean length35
Min length35

Characters and Unicode

Total characters18725
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ’ai pensé que ce serait sans effet
2nd rowJ’ai pensé que ce serait sans effet
3rd rowJ’ai pensé que ce serait sans effet
4th rowJ’ai pensé que ce serait sans effet
5th rowJ’ai pensé que ce serait sans effet

Common Values

ValueCountFrequency (%)
J’ai pensé que ce serait sans effet 535
36.9%
(Missing) 913
63.1%

Length

2023-06-18T04:18:52.099033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:52.317657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
j’ai 535
14.3%
pensé 535
14.3%
que 535
14.3%
ce 535
14.3%
serait 535
14.3%
sans 535
14.3%
effet 535
14.3%

Most occurring characters

ValueCountFrequency (%)
3210
17.1%
e 3210
17.1%
s 2140
11.4%
a 1605
8.6%
i 1070
 
5.7%
n 1070
 
5.7%
t 1070
 
5.7%
f 1070
 
5.7%
J 535
 
2.9%
’ 535
 
2.9%
Other values (6) 3210
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14445
77.1%
Space Separator 3210
 
17.1%
Uppercase Letter 535
 
2.9%
Final Punctuation 535
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3210
22.2%
s 2140
14.8%
a 1605
11.1%
i 1070
 
7.4%
n 1070
 
7.4%
t 1070
 
7.4%
f 1070
 
7.4%
p 535
 
3.7%
é 535
 
3.7%
q 535
 
3.7%
Other values (3) 1605
11.1%
Space Separator
ValueCountFrequency (%)
3210
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 535
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 535
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14980
80.0%
Common 3745
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3210
21.4%
s 2140
14.3%
a 1605
10.7%
i 1070
 
7.1%
n 1070
 
7.1%
t 1070
 
7.1%
f 1070
 
7.1%
J 535
 
3.6%
p 535
 
3.6%
é 535
 
3.6%
Other values (4) 2140
14.3%
Common
ValueCountFrequency (%)
3210
85.7%
’ 535
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17655
94.3%
Punctuation 535
 
2.9%
None 535
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3210
18.2%
e 3210
18.2%
s 2140
12.1%
a 1605
9.1%
i 1070
 
6.1%
n 1070
 
6.1%
t 1070
 
6.1%
f 1070
 
6.1%
J 535
 
3.0%
p 535
 
3.0%
Other values (4) 2140
12.1%
Punctuation
ValueCountFrequency (%)
’ 535
100.0%
None
ValueCountFrequency (%)
é 535
100.0%

securité_dans_espace_public_q17_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing1017
Missing (%)70.2%
Memory size164.9 KiB
J’ai pensé que ce serait trop compliqué / me demanderait trop de temps
431 

Length

Max length70
Median length70
Mean length70
Min length70

Characters and Unicode

Total characters30170
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJ’ai pensé que ce serait trop compliqué / me demanderait trop de temps
2nd rowJ’ai pensé que ce serait trop compliqué / me demanderait trop de temps
3rd rowJ’ai pensé que ce serait trop compliqué / me demanderait trop de temps
4th rowJ’ai pensé que ce serait trop compliqué / me demanderait trop de temps
5th rowJ’ai pensé que ce serait trop compliqué / me demanderait trop de temps

Common Values

ValueCountFrequency (%)
J’ai pensé que ce serait trop compliqué / me demanderait trop de temps 431
29.8%
(Missing) 1017
70.2%

Length

2023-06-18T04:18:52.499403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:52.734495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
trop 862
15.4%
j’ai 431
7.7%
pensé 431
7.7%
que 431
7.7%
ce 431
7.7%
serait 431
7.7%
compliqué 431
7.7%
431
7.7%
me 431
7.7%
demanderait 431
7.7%
Other values (2) 862
15.4%

Most occurring characters

ValueCountFrequency (%)
5172
17.1%
e 3879
12.9%
p 2155
 
7.1%
t 2155
 
7.1%
a 1724
 
5.7%
i 1724
 
5.7%
m 1724
 
5.7%
r 1724
 
5.7%
d 1293
 
4.3%
s 1293
 
4.3%
Other values (10) 7327
24.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23705
78.6%
Space Separator 5172
 
17.1%
Final Punctuation 431
 
1.4%
Other Punctuation 431
 
1.4%
Uppercase Letter 431
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3879
16.4%
p 2155
9.1%
t 2155
9.1%
a 1724
 
7.3%
i 1724
 
7.3%
m 1724
 
7.3%
r 1724
 
7.3%
d 1293
 
5.5%
s 1293
 
5.5%
o 1293
 
5.5%
Other values (6) 4741
20.0%
Space Separator
ValueCountFrequency (%)
5172
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 431
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 431
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 431
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24136
80.0%
Common 6034
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3879
16.1%
p 2155
8.9%
t 2155
8.9%
a 1724
 
7.1%
i 1724
 
7.1%
m 1724
 
7.1%
r 1724
 
7.1%
d 1293
 
5.4%
s 1293
 
5.4%
o 1293
 
5.4%
Other values (7) 5172
21.4%
Common
ValueCountFrequency (%)
5172
85.7%
’ 431
 
7.1%
/ 431
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28877
95.7%
None 862
 
2.9%
Punctuation 431
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5172
17.9%
e 3879
13.4%
p 2155
 
7.5%
t 2155
 
7.5%
a 1724
 
6.0%
i 1724
 
6.0%
m 1724
 
6.0%
r 1724
 
6.0%
d 1293
 
4.5%
s 1293
 
4.5%
Other values (8) 6034
20.9%
None
ValueCountFrequency (%)
é 862
100.0%
Punctuation
ValueCountFrequency (%)
’ 431
100.0%

securité_dans_espace_public_q17_9
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)3.0%
Missing1415
Missing (%)97.7%
Memory size59.8 KiB
Je préfère ne pas répondre
33 

Length

Max length26
Median length26
Mean length26
Min length26

Characters and Unicode

Total characters858
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJe préfère ne pas répondre
2nd rowJe préfère ne pas répondre
3rd rowJe préfère ne pas répondre
4th rowJe préfère ne pas répondre
5th rowJe préfère ne pas répondre

Common Values

ValueCountFrequency (%)
Je préfère ne pas répondre 33
 
2.3%
(Missing) 1415
97.7%

Length

2023-06-18T04:18:52.958306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:53.185473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
je 33
20.0%
préfère 33
20.0%
ne 33
20.0%
pas 33
20.0%
répondre 33
20.0%

Most occurring characters

ValueCountFrequency (%)
e 132
15.4%
132
15.4%
r 132
15.4%
p 99
11.5%
é 66
7.7%
n 66
7.7%
J 33
 
3.8%
f 33
 
3.8%
è 33
 
3.8%
a 33
 
3.8%
Other values (3) 99
11.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 693
80.8%
Space Separator 132
 
15.4%
Uppercase Letter 33
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 132
19.0%
r 132
19.0%
p 99
14.3%
é 66
9.5%
n 66
9.5%
f 33
 
4.8%
è 33
 
4.8%
a 33
 
4.8%
s 33
 
4.8%
o 33
 
4.8%
Space Separator
ValueCountFrequency (%)
132
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 726
84.6%
Common 132
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 132
18.2%
r 132
18.2%
p 99
13.6%
é 66
9.1%
n 66
9.1%
J 33
 
4.5%
f 33
 
4.5%
è 33
 
4.5%
a 33
 
4.5%
s 33
 
4.5%
Other values (2) 66
9.1%
Common
ValueCountFrequency (%)
132
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 759
88.5%
None 99
 
11.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 132
17.4%
132
17.4%
r 132
17.4%
p 99
13.0%
n 66
8.7%
J 33
 
4.3%
f 33
 
4.3%
a 33
 
4.3%
s 33
 
4.3%
o 33
 
4.3%
None
ValueCountFrequency (%)
é 66
66.7%
è 33
33.3%

securité_dans_espace_public_q18
Categorical

HIGH CORRELATION  MISSING 

Distinct4
Distinct (%)6.6%
Missing1387
Missing (%)95.8%
Memory size60.9 KiB
Assez adéquat
21 
Assez inadéquat
19 
Très inadéquat
12 
Très adéquat
9 

Length

Max length15
Median length14
Mean length13.672131
Min length12

Characters and Unicode

Total characters834
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAssez adéquat
2nd rowAssez adéquat
3rd rowTrès inadéquat
4th rowAssez adéquat
5th rowTrès inadéquat

Common Values

ValueCountFrequency (%)
Assez adéquat 21
 
1.5%
Assez inadéquat 19
 
1.3%
Très inadéquat 12
 
0.8%
Très adéquat 9
 
0.6%
(Missing) 1387
95.8%

Length

2023-06-18T04:18:53.400275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:53.668551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
assez 40
32.8%
inadéquat 31
25.4%
adéquat 30
24.6%
très 21
17.2%

Most occurring characters

ValueCountFrequency (%)
a 122
14.6%
s 101
12.1%
q 61
 
7.3%
é 61
 
7.3%
t 61
 
7.3%
u 61
 
7.3%
d 61
 
7.3%
A 40
 
4.8%
z 40
 
4.8%
e 40
 
4.8%
Other values (7) 186
22.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 712
85.4%
Uppercase Letter 61
 
7.3%
Space Separator 61
 
7.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 122
17.1%
s 101
14.2%
q 61
8.6%
é 61
8.6%
t 61
8.6%
u 61
8.6%
d 61
8.6%
z 40
 
5.6%
e 40
 
5.6%
i 31
 
4.4%
Other values (3) 73
10.3%
Uppercase Letter
ValueCountFrequency (%)
A 40
65.6%
T 21
34.4%
Space Separator
ValueCountFrequency (%)
  31
50.8%
30
49.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 773
92.7%
Common 61
 
7.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 122
15.8%
s 101
13.1%
q 61
7.9%
é 61
7.9%
t 61
7.9%
u 61
7.9%
d 61
7.9%
A 40
 
5.2%
z 40
 
5.2%
e 40
 
5.2%
Other values (5) 125
16.2%
Common
ValueCountFrequency (%)
  31
50.8%
30
49.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 721
86.5%
None 113
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 122
16.9%
s 101
14.0%
q 61
8.5%
t 61
8.5%
u 61
8.5%
d 61
8.5%
A 40
 
5.5%
z 40
 
5.5%
e 40
 
5.5%
i 31
 
4.3%
Other values (4) 103
14.3%
None
ValueCountFrequency (%)
é 61
54.0%
  31
27.4%
è 21
 
18.6%

participation_citoyenne_q19
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
1133 
Oui
315 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1133
78.2%
Oui 315
 
21.8%

Length

2023-06-18T04:18:53.905107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:54.160360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1133
78.2%
oui 315
 
21.8%

Most occurring characters

ValueCountFrequency (%)
N 1133
26.1%
o 1133
26.1%
n 1133
26.1%
O 315
 
7.3%
u 315
 
7.3%
i 315
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1133
39.1%
n 1133
39.1%
u 315
 
10.9%
i 315
 
10.9%
Uppercase Letter
ValueCountFrequency (%)
N 1133
78.2%
O 315
 
21.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1133
26.1%
o 1133
26.1%
n 1133
26.1%
O 315
 
7.3%
u 315
 
7.3%
i 315
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1133
26.1%
o 1133
26.1%
n 1133
26.1%
O 315
 
7.3%
u 315
 
7.3%
i 315
 
7.3%

participation_citoyenne_q20
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.6%
Missing1131
Missing (%)78.1%
Memory size62.9 KiB
Non
291 
Oui
 
26

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters951
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 291
 
20.1%
Oui 26
 
1.8%
(Missing) 1131
78.1%

Length

2023-06-18T04:18:54.363006image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:54.613748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 291
91.8%
oui 26
 
8.2%

Most occurring characters

ValueCountFrequency (%)
N 291
30.6%
o 291
30.6%
n 291
30.6%
O 26
 
2.7%
u 26
 
2.7%
i 26
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 634
66.7%
Uppercase Letter 317
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 291
45.9%
n 291
45.9%
u 26
 
4.1%
i 26
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
N 291
91.8%
O 26
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 951
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 291
30.6%
o 291
30.6%
n 291
30.6%
O 26
 
2.7%
u 26
 
2.7%
i 26
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 951
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 291
30.6%
o 291
30.6%
n 291
30.6%
O 26
 
2.7%
u 26
 
2.7%
i 26
 
2.7%

participation_citoyenne_q21_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing1235
Missing (%)85.3%
Memory size123.7 KiB
Crainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle
213 

Length

Max length137
Median length137
Mean length137
Min length137

Characters and Unicode

Total characters29181
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle
2nd rowCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle
3rd rowCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle
4th rowCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle
5th rowCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle

Common Values

ValueCountFrequency (%)
Crainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelle 213
 
14.7%
(Missing) 1235
85.3%

Length

2023-06-18T04:18:54.821530image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:55.082423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 852
18.2%
mon 426
 
9.1%
ou 426
 
9.1%
crainte 213
 
4.5%
orientation 213
 
4.5%
genre 213
 
4.5%
expression 213
 
4.5%
et 213
 
4.5%
identité 213
 
4.5%
en 213
 
4.5%
Other values (7) 1491
31.8%

Most occurring characters

ValueCountFrequency (%)
e 4260
14.6%
4047
13.9%
n 2769
9.5%
i 2343
 
8.0%
o 1917
 
6.6%
t 1917
 
6.6%
r 1917
 
6.6%
d 1491
 
5.1%
a 1278
 
4.4%
s 1065
 
3.6%
Other values (13) 6177
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24495
83.9%
Space Separator 4473
 
15.3%
Uppercase Letter 213
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4260
17.4%
n 2769
11.3%
i 2343
9.6%
o 1917
7.8%
t 1917
7.8%
r 1917
7.8%
d 1491
 
6.1%
a 1278
 
5.2%
s 1065
 
4.3%
u 1065
 
4.3%
Other values (10) 4473
18.3%
Space Separator
ValueCountFrequency (%)
4047
90.5%
  426
 
9.5%
Uppercase Letter
ValueCountFrequency (%)
C 213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24708
84.7%
Common 4473
 
15.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4260
17.2%
n 2769
11.2%
i 2343
9.5%
o 1917
7.8%
t 1917
7.8%
r 1917
7.8%
d 1491
 
6.0%
a 1278
 
5.2%
s 1065
 
4.3%
u 1065
 
4.3%
Other values (11) 4686
19.0%
Common
ValueCountFrequency (%)
4047
90.5%
  426
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27903
95.6%
None 1278
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4260
15.3%
4047
14.5%
n 2769
9.9%
i 2343
8.4%
o 1917
 
6.9%
t 1917
 
6.9%
r 1917
 
6.9%
d 1491
 
5.3%
a 1278
 
4.6%
s 1065
 
3.8%
Other values (11) 4899
17.6%
None
ValueCountFrequency (%)
é 852
66.7%
  426
33.3%

participation_citoyenne_q21_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.3%
Missing1049
Missing (%)72.4%
Memory size128.0 KiB
Crainte que ma réalité ne soit pas comprise ou prise en considération
399 

Length

Max length69
Median length69
Mean length69
Min length69

Characters and Unicode

Total characters27531
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCrainte que ma réalité ne soit pas comprise ou prise en considération
2nd rowCrainte que ma réalité ne soit pas comprise ou prise en considération
3rd rowCrainte que ma réalité ne soit pas comprise ou prise en considération
4th rowCrainte que ma réalité ne soit pas comprise ou prise en considération
5th rowCrainte que ma réalité ne soit pas comprise ou prise en considération

Common Values

ValueCountFrequency (%)
Crainte que ma réalité ne soit pas comprise ou prise en considération 399
 
27.6%
(Missing) 1049
72.4%

Length

2023-06-18T04:18:55.288198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:55.528306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
crainte 399
8.3%
que 399
8.3%
ma 399
8.3%
réalité 399
8.3%
ne 399
8.3%
soit 399
8.3%
pas 399
8.3%
comprise 399
8.3%
ou 399
8.3%
prise 399
8.3%
Other values (2) 798
16.7%

Most occurring characters

ValueCountFrequency (%)
4389
15.9%
i 2793
10.1%
e 2394
8.7%
o 1995
 
7.2%
a 1995
 
7.2%
n 1995
 
7.2%
r 1995
 
7.2%
s 1995
 
7.2%
t 1596
 
5.8%
é 1197
 
4.3%
Other values (8) 5187
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22743
82.6%
Space Separator 4389
 
15.9%
Uppercase Letter 399
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2793
12.3%
e 2394
10.5%
o 1995
8.8%
a 1995
8.8%
n 1995
8.8%
r 1995
8.8%
s 1995
8.8%
t 1596
7.0%
é 1197
 
5.3%
p 1197
 
5.3%
Other values (6) 3591
15.8%
Space Separator
ValueCountFrequency (%)
4389
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23142
84.1%
Common 4389
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 2793
12.1%
e 2394
10.3%
o 1995
8.6%
a 1995
8.6%
n 1995
8.6%
r 1995
8.6%
s 1995
8.6%
t 1596
 
6.9%
é 1197
 
5.2%
p 1197
 
5.2%
Other values (7) 3990
17.2%
Common
ValueCountFrequency (%)
4389
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26334
95.7%
None 1197
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4389
16.7%
i 2793
10.6%
e 2394
9.1%
o 1995
7.6%
a 1995
7.6%
n 1995
7.6%
r 1995
7.6%
s 1995
7.6%
t 1596
 
6.1%
p 1197
 
4.5%
Other values (7) 3990
15.2%
None
ValueCountFrequency (%)
é 1197
100.0%

participation_citoyenne_q21_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing889
Missing (%)61.4%
Memory size100.9 KiB
Horaires inadéquats
559 

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters10621
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHoraires inadéquats
2nd rowHoraires inadéquats
3rd rowHoraires inadéquats
4th rowHoraires inadéquats
5th rowHoraires inadéquats

Common Values

ValueCountFrequency (%)
Horaires inadéquats 559
38.6%
(Missing) 889
61.4%

Length

2023-06-18T04:18:55.724341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:55.952506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
horaires 559
50.0%
inadéquats 559
50.0%

Most occurring characters

ValueCountFrequency (%)
a 1677
15.8%
r 1118
10.5%
i 1118
10.5%
s 1118
10.5%
H 559
 
5.3%
o 559
 
5.3%
e 559
 
5.3%
559
 
5.3%
n 559
 
5.3%
d 559
 
5.3%
Other values (4) 2236
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9503
89.5%
Uppercase Letter 559
 
5.3%
Space Separator 559
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1677
17.6%
r 1118
11.8%
i 1118
11.8%
s 1118
11.8%
o 559
 
5.9%
e 559
 
5.9%
n 559
 
5.9%
d 559
 
5.9%
é 559
 
5.9%
q 559
 
5.9%
Other values (2) 1118
11.8%
Uppercase Letter
ValueCountFrequency (%)
H 559
100.0%
Space Separator
ValueCountFrequency (%)
559
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10062
94.7%
Common 559
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1677
16.7%
r 1118
11.1%
i 1118
11.1%
s 1118
11.1%
H 559
 
5.6%
o 559
 
5.6%
e 559
 
5.6%
n 559
 
5.6%
d 559
 
5.6%
é 559
 
5.6%
Other values (3) 1677
16.7%
Common
ValueCountFrequency (%)
559
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10062
94.7%
None 559
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1677
16.7%
r 1118
11.1%
i 1118
11.1%
s 1118
11.1%
H 559
 
5.6%
o 559
 
5.6%
e 559
 
5.6%
559
 
5.6%
n 559
 
5.6%
d 559
 
5.6%
Other values (3) 1677
16.7%
None
ValueCountFrequency (%)
é 559
100.0%

participation_citoyenne_q21_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing603
Missing (%)41.6%
Memory size83.1 KiB
Manque de temps
845 

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters12675
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManque de temps
2nd rowManque de temps
3rd rowManque de temps
4th rowManque de temps
5th rowManque de temps

Common Values

ValueCountFrequency (%)
Manque de temps 845
58.4%
(Missing) 603
41.6%

Length

2023-06-18T04:18:56.146206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:56.383960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
manque 845
33.3%
de 845
33.3%
temps 845
33.3%

Most occurring characters

ValueCountFrequency (%)
e 2535
20.0%
1690
13.3%
M 845
 
6.7%
a 845
 
6.7%
n 845
 
6.7%
q 845
 
6.7%
u 845
 
6.7%
d 845
 
6.7%
t 845
 
6.7%
m 845
 
6.7%
Other values (2) 1690
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10140
80.0%
Space Separator 1690
 
13.3%
Uppercase Letter 845
 
6.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2535
25.0%
a 845
 
8.3%
n 845
 
8.3%
q 845
 
8.3%
u 845
 
8.3%
d 845
 
8.3%
t 845
 
8.3%
m 845
 
8.3%
p 845
 
8.3%
s 845
 
8.3%
Space Separator
ValueCountFrequency (%)
1690
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 845
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10985
86.7%
Common 1690
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2535
23.1%
M 845
 
7.7%
a 845
 
7.7%
n 845
 
7.7%
q 845
 
7.7%
u 845
 
7.7%
d 845
 
7.7%
t 845
 
7.7%
m 845
 
7.7%
p 845
 
7.7%
Common
ValueCountFrequency (%)
1690
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12675
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2535
20.0%
1690
13.3%
M 845
 
6.7%
a 845
 
6.7%
n 845
 
6.7%
q 845
 
6.7%
u 845
 
6.7%
d 845
 
6.7%
t 845
 
6.7%
m 845
 
6.7%
Other values (2) 1690
13.3%

participation_citoyenne_q21_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.2%
Missing1003
Missing (%)69.3%
Memory size80.2 KiB
Manque de confiance dans le processus
445 

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters16465
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManque de confiance dans le processus
2nd rowManque de confiance dans le processus
3rd rowManque de confiance dans le processus
4th rowManque de confiance dans le processus
5th rowManque de confiance dans le processus

Common Values

ValueCountFrequency (%)
Manque de confiance dans le processus 445
30.7%
(Missing) 1003
69.3%

Length

2023-06-18T04:18:56.575454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:56.822321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
manque 445
16.7%
de 445
16.7%
confiance 445
16.7%
dans 445
16.7%
le 445
16.7%
processus 445
16.7%

Most occurring characters

ValueCountFrequency (%)
e 2225
13.5%
2225
13.5%
n 1780
10.8%
s 1780
10.8%
a 1335
8.1%
c 1335
8.1%
u 890
 
5.4%
d 890
 
5.4%
o 890
 
5.4%
M 445
 
2.7%
Other values (6) 2670
16.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13795
83.8%
Space Separator 2225
 
13.5%
Uppercase Letter 445
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2225
16.1%
n 1780
12.9%
s 1780
12.9%
a 1335
9.7%
c 1335
9.7%
u 890
 
6.5%
d 890
 
6.5%
o 890
 
6.5%
q 445
 
3.2%
f 445
 
3.2%
Other values (4) 1780
12.9%
Space Separator
ValueCountFrequency (%)
2225
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 445
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14240
86.5%
Common 2225
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2225
15.6%
n 1780
12.5%
s 1780
12.5%
a 1335
9.4%
c 1335
9.4%
u 890
 
6.2%
d 890
 
6.2%
o 890
 
6.2%
M 445
 
3.1%
q 445
 
3.1%
Other values (5) 2225
15.6%
Common
ValueCountFrequency (%)
2225
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2225
13.5%
2225
13.5%
n 1780
10.8%
s 1780
10.8%
a 1335
8.1%
c 1335
8.1%
u 890
 
5.4%
d 890
 
5.4%
o 890
 
5.4%
M 445
 
2.7%
Other values (6) 2670
16.2%

participation_citoyenne_q21_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.6%
Missing1273
Missing (%)87.9%
Memory size86.6 KiB
Accessibilité des lieux (ex.: accès à des toilettes non genrées)
175 

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters11200
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAccessibilité des lieux (ex.: accès à des toilettes non genrées)
2nd rowAccessibilité des lieux (ex.: accès à des toilettes non genrées)
3rd rowAccessibilité des lieux (ex.: accès à des toilettes non genrées)
4th rowAccessibilité des lieux (ex.: accès à des toilettes non genrées)
5th rowAccessibilité des lieux (ex.: accès à des toilettes non genrées)

Common Values

ValueCountFrequency (%)
Accessibilité des lieux (ex.: accès à des toilettes non genrées) 175
 
12.1%
(Missing) 1273
87.9%

Length

2023-06-18T04:18:57.045003image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:57.288785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
des 350
20.0%
accessibilité 175
10.0%
lieux 175
10.0%
ex 175
10.0%
accès 175
10.0%
à 175
10.0%
toilettes 175
10.0%
non 175
10.0%
genrées 175
10.0%

Most occurring characters

ValueCountFrequency (%)
e 1575
14.1%
1400
12.5%
s 1225
10.9%
i 875
 
7.8%
c 700
 
6.2%
t 700
 
6.2%
l 525
 
4.7%
n 525
 
4.7%
x 350
 
3.1%
o 350
 
3.1%
Other values (15) 2975
26.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8750
78.1%
Space Separator 1575
 
14.1%
Other Punctuation 350
 
3.1%
Uppercase Letter 175
 
1.6%
Open Punctuation 175
 
1.6%
Close Punctuation 175
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1575
18.0%
s 1225
14.0%
i 875
10.0%
c 700
8.0%
t 700
8.0%
l 525
 
6.0%
n 525
 
6.0%
x 350
 
4.0%
o 350
 
4.0%
é 350
 
4.0%
Other values (8) 1575
18.0%
Space Separator
ValueCountFrequency (%)
1400
88.9%
  175
 
11.1%
Other Punctuation
ValueCountFrequency (%)
: 175
50.0%
. 175
50.0%
Uppercase Letter
ValueCountFrequency (%)
A 175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8925
79.7%
Common 2275
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1575
17.6%
s 1225
13.7%
i 875
9.8%
c 700
 
7.8%
t 700
 
7.8%
l 525
 
5.9%
n 525
 
5.9%
x 350
 
3.9%
o 350
 
3.9%
é 350
 
3.9%
Other values (9) 1750
19.6%
Common
ValueCountFrequency (%)
1400
61.5%
  175
 
7.7%
: 175
 
7.7%
. 175
 
7.7%
( 175
 
7.7%
) 175
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10325
92.2%
None 875
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1575
15.3%
1400
13.6%
s 1225
11.9%
i 875
8.5%
c 700
 
6.8%
t 700
 
6.8%
l 525
 
5.1%
n 525
 
5.1%
x 350
 
3.4%
o 350
 
3.4%
Other values (11) 2100
20.3%
None
ValueCountFrequency (%)
é 350
40.0%
à 175
20.0%
è 175
20.0%
  175
20.0%

participation_citoyenne_q21_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.5%
Missing1241
Missing (%)85.7%
Memory size61.1 KiB
Aucun
207 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1035
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAucun
2nd rowAucun
3rd rowAucun
4th rowAucun
5th rowAucun

Common Values

ValueCountFrequency (%)
Aucun 207
 
14.3%
(Missing) 1241
85.7%

Length

2023-06-18T04:18:57.485963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:18:57.769931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
aucun 207
100.0%

Most occurring characters

ValueCountFrequency (%)
u 414
40.0%
A 207
20.0%
c 207
20.0%
n 207
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 828
80.0%
Uppercase Letter 207
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 414
50.0%
c 207
25.0%
n 207
25.0%
Uppercase Letter
ValueCountFrequency (%)
A 207
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1035
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 414
40.0%
A 207
20.0%
c 207
20.0%
n 207
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1035
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 414
40.0%
A 207
20.0%
c 207
20.0%
n 207
20.0%

piste_action_q22_1
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3411602
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:18:57.952857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.9442489
Coefficient of variation (CV)0.67821706
Kurtosis-1.015484
Mean4.3411602
Median Absolute Deviation (MAD)2
Skewness0.50353762
Sum6286
Variance8.6686018
MonotonicityNot monotonic
2023-06-18T04:18:58.184846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 338
23.3%
2 194
13.4%
4 161
11.1%
3 151
10.4%
6 127
 
8.8%
5 104
 
7.2%
10 101
 
7.0%
7 94
 
6.5%
8 89
 
6.1%
9 89
 
6.1%
ValueCountFrequency (%)
1 338
23.3%
2 194
13.4%
3 151
10.4%
4 161
11.1%
5 104
 
7.2%
6 127
 
8.8%
7 94
 
6.5%
8 89
 
6.1%
9 89
 
6.1%
10 101
 
7.0%
ValueCountFrequency (%)
10 101
 
7.0%
9 89
 
6.1%
8 89
 
6.1%
7 94
 
6.5%
6 127
 
8.8%
5 104
 
7.2%
4 161
11.1%
3 151
10.4%
2 194
13.4%
1 338
23.3%

piste_action_q22_2
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5414365
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:18:58.398335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.0250639
Coefficient of variation (CV)0.66610288
Kurtosis-1.143497
Mean4.5414365
Median Absolute Deviation (MAD)2
Skewness0.46028367
Sum6576
Variance9.1510116
MonotonicityNot monotonic
2023-06-18T04:18:58.668296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 273
18.9%
2 253
17.5%
3 163
11.3%
10 128
8.8%
6 116
8.0%
4 114
7.9%
5 112
7.7%
9 99
 
6.8%
8 95
 
6.6%
7 95
 
6.6%
ValueCountFrequency (%)
1 273
18.9%
2 253
17.5%
3 163
11.3%
4 114
7.9%
5 112
7.7%
6 116
8.0%
7 95
 
6.6%
8 95
 
6.6%
9 99
 
6.8%
10 128
8.8%
ValueCountFrequency (%)
10 128
8.8%
9 99
 
6.8%
8 95
 
6.6%
7 95
 
6.6%
6 116
8.0%
5 112
7.7%
4 114
7.9%
3 163
11.3%
2 253
17.5%
1 273
18.9%

piste_action_q22_3
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3142265
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:18:58.950841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile9
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4548482
Coefficient of variation (CV)0.56901236
Kurtosis-0.5919138
Mean4.3142265
Median Absolute Deviation (MAD)2
Skewness0.5712687
Sum6247
Variance6.0262798
MonotonicityNot monotonic
2023-06-18T04:18:59.317825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3 291
20.1%
2 214
14.8%
4 178
12.3%
1 168
11.6%
5 162
11.2%
6 131
9.0%
7 108
 
7.5%
8 98
 
6.8%
9 50
 
3.5%
10 48
 
3.3%
ValueCountFrequency (%)
1 168
11.6%
2 214
14.8%
3 291
20.1%
4 178
12.3%
5 162
11.2%
6 131
9.0%
7 108
 
7.5%
8 98
 
6.8%
9 50
 
3.5%
10 48
 
3.3%
ValueCountFrequency (%)
10 48
 
3.3%
9 50
 
3.5%
8 98
 
6.8%
7 108
 
7.5%
6 131
9.0%
5 162
11.2%
4 178
12.3%
3 291
20.1%
2 214
14.8%
1 168
11.6%

piste_action_q22_4
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0904696
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:18:59.742224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.6145027
Coefficient of variation (CV)0.42927769
Kurtosis-1.0658467
Mean6.0904696
Median Absolute Deviation (MAD)2
Skewness-0.092183681
Sum8819
Variance6.8356244
MonotonicityNot monotonic
2023-06-18T04:19:00.164856image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4 219
15.1%
10 186
12.8%
8 168
11.6%
7 168
11.6%
5 167
11.5%
9 147
10.2%
6 138
9.5%
3 122
8.4%
2 78
 
5.4%
1 55
 
3.8%
ValueCountFrequency (%)
1 55
 
3.8%
2 78
 
5.4%
3 122
8.4%
4 219
15.1%
5 167
11.5%
6 138
9.5%
7 168
11.6%
8 168
11.6%
9 147
10.2%
10 186
12.8%
ValueCountFrequency (%)
10 186
12.8%
9 147
10.2%
8 168
11.6%
7 168
11.6%
6 138
9.5%
5 167
11.5%
4 219
15.1%
3 122
8.4%
2 78
 
5.4%
1 55
 
3.8%

piste_action_q22_5
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4240331
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:00.517671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median5
Q37
95-th percentile9
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3975402
Coefficient of variation (CV)0.44202166
Kurtosis-0.7537591
Mean5.4240331
Median Absolute Deviation (MAD)2
Skewness0.029060987
Sum7854
Variance5.7481988
MonotonicityNot monotonic
2023-06-18T04:19:00.952586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
5 283
19.5%
6 181
12.5%
4 178
12.3%
7 166
11.5%
8 146
10.1%
3 124
8.6%
2 115
7.9%
9 103
 
7.1%
1 82
 
5.7%
10 70
 
4.8%
ValueCountFrequency (%)
1 82
 
5.7%
2 115
7.9%
3 124
8.6%
4 178
12.3%
5 283
19.5%
6 181
12.5%
7 166
11.5%
8 146
10.1%
9 103
 
7.1%
10 70
 
4.8%
ValueCountFrequency (%)
10 70
 
4.8%
9 103
 
7.1%
8 146
10.1%
7 166
11.5%
6 181
12.5%
5 283
19.5%
4 178
12.3%
3 124
8.6%
2 115
7.9%
1 82
 
5.7%

piste_action_q22_6
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5462707
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:01.383415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q37
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.3905047
Coefficient of variation (CV)0.43101118
Kurtosis-0.76104024
Mean5.5462707
Median Absolute Deviation (MAD)2
Skewness-0.038613726
Sum8031
Variance5.7145127
MonotonicityNot monotonic
2023-06-18T04:19:01.821287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6 305
21.1%
7 186
12.8%
4 159
11.0%
5 159
11.0%
3 149
10.3%
8 119
 
8.2%
2 116
 
8.0%
9 110
 
7.6%
10 78
 
5.4%
1 67
 
4.6%
ValueCountFrequency (%)
1 67
 
4.6%
2 116
 
8.0%
3 149
10.3%
4 159
11.0%
5 159
11.0%
6 305
21.1%
7 186
12.8%
8 119
 
8.2%
9 110
 
7.6%
10 78
 
5.4%
ValueCountFrequency (%)
10 78
 
5.4%
9 110
 
7.6%
8 119
 
8.2%
7 186
12.8%
6 305
21.1%
5 159
11.0%
4 159
11.0%
3 149
10.3%
2 116
 
8.0%
1 67
 
4.6%

piste_action_q22_7
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1698895
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:02.238316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median7
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.4251343
Coefficient of variation (CV)0.39305961
Kurtosis-0.72015857
Mean6.1698895
Median Absolute Deviation (MAD)2
Skewness-0.45563004
Sum8934
Variance5.8812766
MonotonicityNot monotonic
2023-06-18T04:19:02.443142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
7 307
21.2%
8 208
14.4%
9 189
13.1%
6 154
10.6%
4 134
9.3%
5 131
9.0%
3 98
 
6.8%
2 91
 
6.3%
10 77
 
5.3%
1 59
 
4.1%
ValueCountFrequency (%)
1 59
 
4.1%
2 91
 
6.3%
3 98
 
6.8%
4 134
9.3%
5 131
9.0%
6 154
10.6%
7 307
21.2%
8 208
14.4%
9 189
13.1%
10 77
 
5.3%
ValueCountFrequency (%)
10 77
 
5.3%
9 189
13.1%
8 208
14.4%
7 307
21.2%
6 154
10.6%
5 131
9.0%
4 134
9.3%
3 98
 
6.8%
2 91
 
6.3%
1 59
 
4.1%

piste_action_q22_8
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.1719613
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:02.653933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.7231356
Coefficient of variation (CV)0.44121074
Kurtosis-1.0342504
Mean6.1719613
Median Absolute Deviation (MAD)2
Skewness-0.42488536
Sum8937
Variance7.4154676
MonotonicityNot monotonic
2023-06-18T04:19:02.866935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
8 301
20.8%
9 204
14.1%
7 144
9.9%
5 138
9.5%
10 121
8.4%
6 117
 
8.1%
3 113
 
7.8%
4 109
 
7.5%
2 107
 
7.4%
1 94
 
6.5%
ValueCountFrequency (%)
1 94
 
6.5%
2 107
 
7.4%
3 113
 
7.8%
4 109
 
7.5%
5 138
9.5%
6 117
 
8.1%
7 144
9.9%
8 301
20.8%
9 204
14.1%
10 121
8.4%
ValueCountFrequency (%)
10 121
8.4%
9 204
14.1%
8 301
20.8%
7 144
9.9%
6 117
 
8.1%
5 138
9.5%
4 109
 
7.5%
3 113
 
7.8%
2 107
 
7.4%
1 94
 
6.5%

piste_action_q22_9
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3957182
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:03.091400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.795773
Coefficient of variation (CV)0.37802589
Kurtosis-0.50323545
Mean7.3957182
Median Absolute Deviation (MAD)1
Skewness-0.92084556
Sum10709
Variance7.8163465
MonotonicityNot monotonic
2023-06-18T04:19:03.304176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
10 397
27.4%
9 381
26.3%
8 132
 
9.1%
2 92
 
6.4%
7 89
 
6.1%
5 80
 
5.5%
6 80
 
5.5%
3 77
 
5.3%
4 72
 
5.0%
1 48
 
3.3%
ValueCountFrequency (%)
1 48
 
3.3%
2 92
 
6.4%
3 77
 
5.3%
4 72
 
5.0%
5 80
 
5.5%
6 80
 
5.5%
7 89
 
6.1%
8 132
 
9.1%
9 381
26.3%
10 397
27.4%
ValueCountFrequency (%)
10 397
27.4%
9 381
26.3%
8 132
 
9.1%
7 89
 
6.1%
6 80
 
5.5%
5 80
 
5.5%
4 72
 
5.0%
3 77
 
5.3%
2 92
 
6.4%
1 48
 
3.3%

piste_action_q22_10
Real number (ℝ)

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0048343
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size11.4 KiB
2023-06-18T04:19:03.511431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q38
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2450021
Coefficient of variation (CV)0.64837355
Kurtosis-1.3482192
Mean5.0048343
Median Absolute Deviation (MAD)3
Skewness0.30031014
Sum7247
Variance10.530039
MonotonicityNot monotonic
2023-06-18T04:19:03.716710image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 264
18.2%
10 242
16.7%
2 188
13.0%
3 160
11.0%
4 124
8.6%
5 112
7.7%
6 99
 
6.8%
8 92
 
6.4%
7 91
 
6.3%
9 76
 
5.2%
ValueCountFrequency (%)
1 264
18.2%
2 188
13.0%
3 160
11.0%
4 124
8.6%
5 112
7.7%
6 99
 
6.8%
7 91
 
6.3%
8 92
 
6.4%
9 76
 
5.2%
10 242
16.7%
ValueCountFrequency (%)
10 242
16.7%
9 76
 
5.2%
8 92
 
6.4%
7 91
 
6.3%
6 99
 
6.8%
5 112
7.7%
4 124
8.6%
3 160
11.0%
2 188
13.0%
1 264
18.2%

piste_action_q23_1
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing450
Missing (%)31.1%
Memory size215.5 KiB
À travers l’art (mural, festival, etc.)
998 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters38922
Distinct characters19
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers l’art (mural, festival, etc.)
2nd rowÀ travers l’art (mural, festival, etc.)
3rd rowÀ travers l’art (mural, festival, etc.)
4th rowÀ travers l’art (mural, festival, etc.)
5th rowÀ travers l’art (mural, festival, etc.)

Common Values

ValueCountFrequency (%)
À travers l’art (mural, festival, etc.) 998
68.9%
(Missing) 450
31.1%

Length

2023-06-18T04:19:03.950149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:04.165045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
à 998
16.7%
travers 998
16.7%
l’art 998
16.7%
mural 998
16.7%
festival 998
16.7%
etc 998
16.7%

Most occurring characters

ValueCountFrequency (%)
4990
12.8%
t 3992
10.3%
r 3992
10.3%
a 3992
10.3%
e 2994
 
7.7%
l 2994
 
7.7%
v 1996
 
5.1%
s 1996
 
5.1%
, 1996
 
5.1%
À 998
 
2.6%
Other values (9) 8982
23.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26946
69.2%
Space Separator 4990
 
12.8%
Other Punctuation 2994
 
7.7%
Uppercase Letter 998
 
2.6%
Final Punctuation 998
 
2.6%
Open Punctuation 998
 
2.6%
Close Punctuation 998
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 3992
14.8%
r 3992
14.8%
a 3992
14.8%
e 2994
11.1%
l 2994
11.1%
v 1996
7.4%
s 1996
7.4%
f 998
 
3.7%
c 998
 
3.7%
i 998
 
3.7%
Other values (2) 1996
7.4%
Other Punctuation
ValueCountFrequency (%)
, 1996
66.7%
. 998
33.3%
Space Separator
ValueCountFrequency (%)
4990
100.0%
Uppercase Letter
ValueCountFrequency (%)
À 998
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 998
100.0%
Open Punctuation
ValueCountFrequency (%)
( 998
100.0%
Close Punctuation
ValueCountFrequency (%)
) 998
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27944
71.8%
Common 10978
 
28.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 3992
14.3%
r 3992
14.3%
a 3992
14.3%
e 2994
10.7%
l 2994
10.7%
v 1996
7.1%
s 1996
7.1%
À 998
 
3.6%
f 998
 
3.6%
c 998
 
3.6%
Other values (3) 2994
10.7%
Common
ValueCountFrequency (%)
4990
45.5%
, 1996
 
18.2%
. 998
 
9.1%
’ 998
 
9.1%
( 998
 
9.1%
) 998
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36926
94.9%
None 998
 
2.6%
Punctuation 998
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4990
13.5%
t 3992
10.8%
r 3992
10.8%
a 3992
10.8%
e 2994
8.1%
l 2994
8.1%
v 1996
 
5.4%
s 1996
 
5.4%
, 1996
 
5.4%
f 998
 
2.7%
Other values (7) 6986
18.9%
None
ValueCountFrequency (%)
À 998
100.0%
Punctuation
ValueCountFrequency (%)
’ 998
100.0%

piste_action_q23_2
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing583
Missing (%)40.3%
Memory size192.7 KiB
À travers le nom des rues, des parcs ou des espaces publics
865 

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters51035
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers le nom des rues, des parcs ou des espaces publics
2nd rowÀ travers le nom des rues, des parcs ou des espaces publics
3rd rowÀ travers le nom des rues, des parcs ou des espaces publics
4th rowÀ travers le nom des rues, des parcs ou des espaces publics
5th rowÀ travers le nom des rues, des parcs ou des espaces publics

Common Values

ValueCountFrequency (%)
À travers le nom des rues, des parcs ou des espaces publics 865
59.7%
(Missing) 583
40.3%

Length

2023-06-18T04:19:04.353214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:04.591259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
des 2595
25.0%
à 865
 
8.3%
travers 865
 
8.3%
le 865
 
8.3%
nom 865
 
8.3%
rues 865
 
8.3%
parcs 865
 
8.3%
ou 865
 
8.3%
espaces 865
 
8.3%
publics 865
 
8.3%

Most occurring characters

ValueCountFrequency (%)
9515
18.6%
s 7785
15.3%
e 6920
13.6%
r 3460
 
6.8%
a 2595
 
5.1%
c 2595
 
5.1%
p 2595
 
5.1%
d 2595
 
5.1%
u 2595
 
5.1%
l 1730
 
3.4%
Other values (9) 8650
16.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39790
78.0%
Space Separator 9515
 
18.6%
Uppercase Letter 865
 
1.7%
Other Punctuation 865
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 7785
19.6%
e 6920
17.4%
r 3460
8.7%
a 2595
 
6.5%
c 2595
 
6.5%
p 2595
 
6.5%
d 2595
 
6.5%
u 2595
 
6.5%
l 1730
 
4.3%
o 1730
 
4.3%
Other values (6) 5190
13.0%
Space Separator
ValueCountFrequency (%)
9515
100.0%
Uppercase Letter
ValueCountFrequency (%)
À 865
100.0%
Other Punctuation
ValueCountFrequency (%)
, 865
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40655
79.7%
Common 10380
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 7785
19.1%
e 6920
17.0%
r 3460
8.5%
a 2595
 
6.4%
c 2595
 
6.4%
p 2595
 
6.4%
d 2595
 
6.4%
u 2595
 
6.4%
l 1730
 
4.3%
o 1730
 
4.3%
Other values (7) 6055
14.9%
Common
ValueCountFrequency (%)
9515
91.7%
, 865
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50170
98.3%
None 865
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9515
19.0%
s 7785
15.5%
e 6920
13.8%
r 3460
 
6.9%
a 2595
 
5.2%
c 2595
 
5.2%
p 2595
 
5.2%
d 2595
 
5.2%
u 2595
 
5.2%
l 1730
 
3.4%
Other values (8) 7785
15.5%
None
ValueCountFrequency (%)
À 865
100.0%

piste_action_q23_3
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing429
Missing (%)29.6%
Memory size278.6 KiB
À travers des campagnes d’information et de sensibilisation
1019 

Length

Max length59
Median length59
Mean length59
Min length59

Characters and Unicode

Total characters60121
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers des campagnes d’information et de sensibilisation
2nd rowÀ travers des campagnes d’information et de sensibilisation
3rd rowÀ travers des campagnes d’information et de sensibilisation
4th rowÀ travers des campagnes d’information et de sensibilisation
5th rowÀ travers des campagnes d’information et de sensibilisation

Common Values

ValueCountFrequency (%)
À travers des campagnes d’information et de sensibilisation 1019
70.4%
(Missing) 429
29.6%

Length

2023-06-18T04:19:04.806352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:05.032228image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
à 1019
12.5%
travers 1019
12.5%
des 1019
12.5%
campagnes 1019
12.5%
d’information 1019
12.5%
et 1019
12.5%
de 1019
12.5%
sensibilisation 1019
12.5%

Most occurring characters

ValueCountFrequency (%)
7133
11.9%
e 6114
10.2%
s 6114
10.2%
i 6114
10.2%
a 5095
8.5%
n 5095
8.5%
t 4076
 
6.8%
r 3057
 
5.1%
d 3057
 
5.1%
o 3057
 
5.1%
Other values (10) 11209
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 50950
84.7%
Space Separator 7133
 
11.9%
Final Punctuation 1019
 
1.7%
Uppercase Letter 1019
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6114
12.0%
s 6114
12.0%
i 6114
12.0%
a 5095
10.0%
n 5095
10.0%
t 4076
8.0%
r 3057
6.0%
d 3057
6.0%
o 3057
6.0%
m 2038
 
4.0%
Other values (7) 7133
14.0%
Space Separator
ValueCountFrequency (%)
7133
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1019
100.0%
Uppercase Letter
ValueCountFrequency (%)
À 1019
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 51969
86.4%
Common 8152
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6114
11.8%
s 6114
11.8%
i 6114
11.8%
a 5095
9.8%
n 5095
9.8%
t 4076
7.8%
r 3057
 
5.9%
d 3057
 
5.9%
o 3057
 
5.9%
m 2038
 
3.9%
Other values (8) 8152
15.7%
Common
ValueCountFrequency (%)
7133
87.5%
’ 1019
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58083
96.6%
Punctuation 1019
 
1.7%
None 1019
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7133
12.3%
e 6114
10.5%
s 6114
10.5%
i 6114
10.5%
a 5095
8.8%
n 5095
8.8%
t 4076
7.0%
r 3057
 
5.3%
d 3057
 
5.3%
o 3057
 
5.3%
Other values (8) 9171
15.8%
Punctuation
ValueCountFrequency (%)
’ 1019
100.0%
None
ValueCountFrequency (%)
À 1019
100.0%

piste_action_q23_4
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing442
Missing (%)30.5%
Memory size191.3 KiB
À travers des événements soutenus par la Ville
1006 

Length

Max length46
Median length46
Mean length46
Min length46

Characters and Unicode

Total characters46276
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers des événements soutenus par la Ville
2nd rowÀ travers des événements soutenus par la Ville
3rd rowÀ travers des événements soutenus par la Ville
4th rowÀ travers des événements soutenus par la Ville
5th rowÀ travers des événements soutenus par la Ville

Common Values

ValueCountFrequency (%)
À travers des événements soutenus par la Ville 1006
69.5%
(Missing) 442
30.5%

Length

2023-06-18T04:19:05.220354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:05.447603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
à 1006
12.5%
travers 1006
12.5%
des 1006
12.5%
événements 1006
12.5%
soutenus 1006
12.5%
par 1006
12.5%
la 1006
12.5%
ville 1006
12.5%

Most occurring characters

ValueCountFrequency (%)
7042
15.2%
e 6036
13.0%
s 5030
10.9%
t 3018
 
6.5%
r 3018
 
6.5%
a 3018
 
6.5%
n 3018
 
6.5%
l 3018
 
6.5%
é 2012
 
4.3%
u 2012
 
4.3%
Other values (8) 9054
19.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 37222
80.4%
Space Separator 7042
 
15.2%
Uppercase Letter 2012
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6036
16.2%
s 5030
13.5%
t 3018
8.1%
r 3018
8.1%
a 3018
8.1%
n 3018
8.1%
l 3018
8.1%
é 2012
 
5.4%
u 2012
 
5.4%
v 2012
 
5.4%
Other values (5) 5030
13.5%
Uppercase Letter
ValueCountFrequency (%)
V 1006
50.0%
À 1006
50.0%
Space Separator
ValueCountFrequency (%)
7042
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39234
84.8%
Common 7042
 
15.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6036
15.4%
s 5030
12.8%
t 3018
7.7%
r 3018
7.7%
a 3018
7.7%
n 3018
7.7%
l 3018
7.7%
é 2012
 
5.1%
u 2012
 
5.1%
v 2012
 
5.1%
Other values (7) 7042
17.9%
Common
ValueCountFrequency (%)
7042
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43258
93.5%
None 3018
 
6.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7042
16.3%
e 6036
14.0%
s 5030
11.6%
t 3018
7.0%
r 3018
7.0%
a 3018
7.0%
n 3018
7.0%
l 3018
7.0%
u 2012
 
4.7%
v 2012
 
4.7%
Other values (6) 6036
14.0%
None
ValueCountFrequency (%)
é 2012
66.7%
À 1006
33.3%

piste_action_q23_5
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing514
Missing (%)35.5%
Memory size285.6 KiB
À travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)
934 

Length

Max length103
Median length103
Mean length103
Min length103

Characters and Unicode

Total characters96202
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)
2nd rowÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)
3rd rowÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)
4th rowÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)
5th rowÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)

Common Values

ValueCountFrequency (%)
À travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.) 934
64.5%
(Missing) 514
35.5%

Length

2023-06-18T04:19:05.638981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:05.862237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
des 1868
15.4%
à 934
7.7%
travers 934
7.7%
communications 934
7.7%
plus 934
7.7%
inclusives 934
7.7%
communautés 934
7.7%
lgbtq 934
7.7%
publications 934
7.7%
web 934
7.7%
Other values (2) 1868
15.4%

Most occurring characters

ValueCountFrequency (%)
11208
 
11.7%
s 9340
 
9.7%
i 6538
 
6.8%
u 5604
 
5.8%
t 5604
 
5.8%
e 5604
 
5.8%
c 5604
 
5.8%
n 5604
 
5.8%
a 4670
 
4.9%
m 3736
 
3.9%
Other values (20) 32690
34.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 73786
76.7%
Space Separator 11208
 
11.7%
Uppercase Letter 5604
 
5.8%
Other Punctuation 2802
 
2.9%
Math Symbol 934
 
1.0%
Open Punctuation 934
 
1.0%
Close Punctuation 934
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 9340
12.7%
i 6538
 
8.9%
u 5604
 
7.6%
t 5604
 
7.6%
e 5604
 
7.6%
c 5604
 
7.6%
n 5604
 
7.6%
a 4670
 
6.3%
m 3736
 
5.1%
l 3736
 
5.1%
Other values (8) 17746
24.1%
Uppercase Letter
ValueCountFrequency (%)
À 934
16.7%
Q 934
16.7%
T 934
16.7%
B 934
16.7%
G 934
16.7%
L 934
16.7%
Other Punctuation
ValueCountFrequency (%)
, 1868
66.7%
. 934
33.3%
Space Separator
ValueCountFrequency (%)
11208
100.0%
Math Symbol
ValueCountFrequency (%)
+ 934
100.0%
Open Punctuation
ValueCountFrequency (%)
( 934
100.0%
Close Punctuation
ValueCountFrequency (%)
) 934
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79390
82.5%
Common 16812
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 9340
 
11.8%
i 6538
 
8.2%
u 5604
 
7.1%
t 5604
 
7.1%
e 5604
 
7.1%
c 5604
 
7.1%
n 5604
 
7.1%
a 4670
 
5.9%
m 3736
 
4.7%
l 3736
 
4.7%
Other values (14) 23350
29.4%
Common
ValueCountFrequency (%)
11208
66.7%
, 1868
 
11.1%
+ 934
 
5.6%
. 934
 
5.6%
( 934
 
5.6%
) 934
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93400
97.1%
None 2802
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11208
 
12.0%
s 9340
 
10.0%
i 6538
 
7.0%
u 5604
 
6.0%
t 5604
 
6.0%
e 5604
 
6.0%
c 5604
 
6.0%
n 5604
 
6.0%
a 4670
 
5.0%
m 3736
 
4.0%
Other values (18) 29888
32.0%
None
ValueCountFrequency (%)
é 1868
66.7%
À 934
33.3%

piste_action_q23_6
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing597
Missing (%)41.2%
Memory size243.7 KiB
À travers une plus grande représentation municipale aux événements des communautés LGBTQ+
851 

Length

Max length89
Median length89
Mean length89
Min length89

Characters and Unicode

Total characters75739
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+
2nd rowÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+
3rd rowÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+
4th rowÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+
5th rowÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+

Common Values

ValueCountFrequency (%)
À travers une plus grande représentation municipale aux événements des communautés LGBTQ+ 851
58.8%
(Missing) 597
41.2%

Length

2023-06-18T04:19:06.051946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:06.289196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
à 851
8.3%
travers 851
8.3%
une 851
8.3%
plus 851
8.3%
grande 851
8.3%
représentation 851
8.3%
municipale 851
8.3%
aux 851
8.3%
événements 851
8.3%
des 851
8.3%
Other values (2) 1702
16.7%

Most occurring characters

ValueCountFrequency (%)
9361
12.4%
e 7659
 
10.1%
n 6808
 
9.0%
a 5106
 
6.7%
s 5106
 
6.7%
u 5106
 
6.7%
t 4255
 
5.6%
r 4255
 
5.6%
é 3404
 
4.5%
m 3404
 
4.5%
Other values (16) 21275
28.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60421
79.8%
Space Separator 9361
 
12.4%
Uppercase Letter 5106
 
6.7%
Math Symbol 851
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7659
12.7%
n 6808
11.3%
a 5106
 
8.5%
s 5106
 
8.5%
u 5106
 
8.5%
t 4255
 
7.0%
r 4255
 
7.0%
é 3404
 
5.6%
m 3404
 
5.6%
p 2553
 
4.2%
Other values (8) 12765
21.1%
Uppercase Letter
ValueCountFrequency (%)
Q 851
16.7%
G 851
16.7%
T 851
16.7%
B 851
16.7%
À 851
16.7%
L 851
16.7%
Space Separator
ValueCountFrequency (%)
9361
100.0%
Math Symbol
ValueCountFrequency (%)
+ 851
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 65527
86.5%
Common 10212
 
13.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7659
11.7%
n 6808
 
10.4%
a 5106
 
7.8%
s 5106
 
7.8%
u 5106
 
7.8%
t 4255
 
6.5%
r 4255
 
6.5%
é 3404
 
5.2%
m 3404
 
5.2%
p 2553
 
3.9%
Other values (14) 17871
27.3%
Common
ValueCountFrequency (%)
9361
91.7%
+ 851
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71484
94.4%
None 4255
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9361
13.1%
e 7659
10.7%
n 6808
 
9.5%
a 5106
 
7.1%
s 5106
 
7.1%
u 5106
 
7.1%
t 4255
 
6.0%
r 4255
 
6.0%
m 3404
 
4.8%
p 2553
 
3.6%
Other values (14) 17871
25.0%
None
ValueCountFrequency (%)
é 3404
80.0%
À 851
 
20.0%

piste_action_q23_7
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing419
Missing (%)28.9%
Memory size246.6 KiB
En invitant les organismes LGBTQ+ aux événements de la Ville de Montréal
1029 

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters74088
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEn invitant les organismes LGBTQ+ aux événements de la Ville de Montréal
2nd rowEn invitant les organismes LGBTQ+ aux événements de la Ville de Montréal
3rd rowEn invitant les organismes LGBTQ+ aux événements de la Ville de Montréal
4th rowEn invitant les organismes LGBTQ+ aux événements de la Ville de Montréal
5th rowEn invitant les organismes LGBTQ+ aux événements de la Ville de Montréal

Common Values

ValueCountFrequency (%)
En invitant les organismes LGBTQ+ aux événements de la Ville de Montréal 1029
71.1%
(Missing) 419
28.9%

Length

2023-06-18T04:19:06.510677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:06.733936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 2058
16.7%
en 1029
8.3%
invitant 1029
8.3%
les 1029
8.3%
organismes 1029
8.3%
lgbtq 1029
8.3%
aux 1029
8.3%
événements 1029
8.3%
la 1029
8.3%
ville 1029
8.3%

Most occurring characters

ValueCountFrequency (%)
11319
15.3%
e 7203
 
9.7%
n 7203
 
9.7%
a 5145
 
6.9%
l 5145
 
6.9%
s 4116
 
5.6%
i 4116
 
5.6%
t 4116
 
5.6%
é 3087
 
4.2%
r 2058
 
2.8%
Other values (16) 20580
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 53508
72.2%
Space Separator 11319
 
15.3%
Uppercase Letter 8232
 
11.1%
Math Symbol 1029
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7203
13.5%
n 7203
13.5%
a 5145
9.6%
l 5145
9.6%
s 4116
7.7%
i 4116
7.7%
t 4116
7.7%
é 3087
 
5.8%
r 2058
 
3.8%
d 2058
 
3.8%
Other values (6) 9261
17.3%
Uppercase Letter
ValueCountFrequency (%)
V 1029
12.5%
E 1029
12.5%
Q 1029
12.5%
T 1029
12.5%
B 1029
12.5%
G 1029
12.5%
L 1029
12.5%
M 1029
12.5%
Space Separator
ValueCountFrequency (%)
11319
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1029
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 61740
83.3%
Common 12348
 
16.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7203
11.7%
n 7203
11.7%
a 5145
 
8.3%
l 5145
 
8.3%
s 4116
 
6.7%
i 4116
 
6.7%
t 4116
 
6.7%
é 3087
 
5.0%
r 2058
 
3.3%
d 2058
 
3.3%
Other values (14) 17493
28.3%
Common
ValueCountFrequency (%)
11319
91.7%
+ 1029
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71001
95.8%
None 3087
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11319
15.9%
e 7203
 
10.1%
n 7203
 
10.1%
a 5145
 
7.2%
l 5145
 
7.2%
s 4116
 
5.8%
i 4116
 
5.8%
t 4116
 
5.8%
r 2058
 
2.9%
d 2058
 
2.9%
Other values (15) 18522
26.1%
None
ValueCountFrequency (%)
é 3087
100.0%

piste_action_q23_8
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing648
Missing (%)44.8%
Memory size244.2 KiB
En identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+
800 

Length

Max length98
Median length98
Mean length98
Min length98

Characters and Unicode

Total characters78400
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+
2nd rowEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+
3rd rowEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+
4th rowEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+
5th rowEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+

Common Values

ValueCountFrequency (%)
En identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+ 800
55.2%
(Missing) 648
44.8%

Length

2023-06-18T04:19:06.926798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:07.166982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 2400
17.6%
en 800
 
5.9%
identifiant 800
 
5.9%
une 800
 
5.9%
personne 800
 
5.9%
la 800
 
5.9%
ville 800
 
5.9%
montréal 800
 
5.9%
chargée 800
 
5.9%
porter 800
 
5.9%
Other values (5) 4000
29.4%

Most occurring characters

ValueCountFrequency (%)
12800
16.3%
e 12000
15.3%
n 6400
 
8.2%
d 4800
 
6.1%
r 4800
 
6.1%
l 4000
 
5.1%
i 4000
 
5.1%
s 3200
 
4.1%
t 3200
 
4.1%
a 3200
 
4.1%
Other values (19) 20000
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 58400
74.5%
Space Separator 12800
 
16.3%
Uppercase Letter 6400
 
8.2%
Math Symbol 800
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 12000
20.5%
n 6400
11.0%
d 4800
 
8.2%
r 4800
 
8.2%
l 4000
 
6.8%
i 4000
 
6.8%
s 3200
 
5.5%
t 3200
 
5.5%
a 3200
 
5.5%
o 3200
 
5.5%
Other values (9) 9600
16.4%
Uppercase Letter
ValueCountFrequency (%)
T 800
12.5%
B 800
12.5%
Q 800
12.5%
G 800
12.5%
L 800
12.5%
E 800
12.5%
M 800
12.5%
V 800
12.5%
Space Separator
ValueCountFrequency (%)
12800
100.0%
Math Symbol
ValueCountFrequency (%)
+ 800
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 64800
82.7%
Common 13600
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 12000
18.5%
n 6400
 
9.9%
d 4800
 
7.4%
r 4800
 
7.4%
l 4000
 
6.2%
i 4000
 
6.2%
s 3200
 
4.9%
t 3200
 
4.9%
a 3200
 
4.9%
o 3200
 
4.9%
Other values (17) 16000
24.7%
Common
ValueCountFrequency (%)
12800
94.1%
+ 800
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76800
98.0%
None 1600
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12800
16.7%
e 12000
15.6%
n 6400
 
8.3%
d 4800
 
6.2%
r 4800
 
6.2%
l 4000
 
5.2%
i 4000
 
5.2%
s 3200
 
4.2%
t 3200
 
4.2%
a 3200
 
4.2%
Other values (18) 18400
24.0%
None
ValueCountFrequency (%)
é 1600
100.0%

profil_q25
Categorical

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size162.8 KiB
Page Facebook de la Ville
644 
Par le biais d’un organisme ou d’une association
227 
Autres (veuillez préciser)
211 
Par une personne de mon entourage
194 
Site web de la Ville
105 
Other values (2)
67 

Length

Max length48
Median length41
Mean length29.332182
Min length7

Characters and Unicode

Total characters42473
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAutres (veuillez préciser)
2nd rowPar le biais d’un organisme ou d’une association
3rd rowPar une personne de mon entourage
4th rowPar une personne de mon entourage
5th rowInvitation de la Ville reçue par courriel

Common Values

ValueCountFrequency (%)
Page Facebook de la Ville 644
44.5%
Par le biais d’un organisme ou d’une association 227
 
15.7%
Autres (veuillez préciser) 211
 
14.6%
Par une personne de mon entourage 194
 
13.4%
Site web de la Ville 105
 
7.3%
Twitter 37
 
2.6%
Invitation de la Ville reçue par courriel 30
 
2.1%

Length

2023-06-18T04:19:07.397482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:07.681838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
de 973
12.8%
la 779
 
10.2%
ville 779
 
10.2%
page 644
 
8.5%
facebook 644
 
8.5%
par 451
 
5.9%
le 227
 
3.0%
biais 227
 
3.0%
d’un 227
 
3.0%
organisme 227
 
3.0%
Other values (16) 2427
31.9%

Most occurring characters

ValueCountFrequency (%)
6157
14.5%
e 5872
13.8%
a 3650
 
8.6%
l 3016
 
7.1%
o 2838
 
6.7%
i 2568
 
6.0%
n 1938
 
4.6%
r 1826
 
4.3%
u 1551
 
3.7%
s 1524
 
3.6%
Other values (23) 11533
27.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32569
76.7%
Space Separator 6157
 
14.5%
Uppercase Letter 2871
 
6.8%
Final Punctuation 454
 
1.1%
Open Punctuation 211
 
0.5%
Close Punctuation 211
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5872
18.0%
a 3650
11.2%
l 3016
9.3%
o 2838
8.7%
i 2568
7.9%
n 1938
 
6.0%
r 1826
 
5.6%
u 1551
 
4.8%
s 1524
 
4.7%
d 1427
 
4.4%
Other values (12) 6359
19.5%
Uppercase Letter
ValueCountFrequency (%)
P 1065
37.1%
V 779
27.1%
F 644
22.4%
A 211
 
7.3%
S 105
 
3.7%
T 37
 
1.3%
I 30
 
1.0%
Space Separator
ValueCountFrequency (%)
6157
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 454
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 35440
83.4%
Common 7033
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5872
16.6%
a 3650
 
10.3%
l 3016
 
8.5%
o 2838
 
8.0%
i 2568
 
7.2%
n 1938
 
5.5%
r 1826
 
5.2%
u 1551
 
4.4%
s 1524
 
4.3%
d 1427
 
4.0%
Other values (19) 9230
26.0%
Common
ValueCountFrequency (%)
6157
87.5%
’ 454
 
6.5%
( 211
 
3.0%
) 211
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 41778
98.4%
Punctuation 454
 
1.1%
None 241
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6157
14.7%
e 5872
14.1%
a 3650
 
8.7%
l 3016
 
7.2%
o 2838
 
6.8%
i 2568
 
6.1%
n 1938
 
4.6%
r 1826
 
4.4%
u 1551
 
3.7%
s 1524
 
3.6%
Other values (20) 10838
25.9%
Punctuation
ValueCountFrequency (%)
’ 454
100.0%
None
ValueCountFrequency (%)
é 211
87.6%
ç 30
 
12.4%

profil_q26
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size133.2 KiB
Plus de 20 ans
466 
4 à 10 ans
352 
11 à 20 ans
326 
1 à 3 ans
218 
Moins d’un an
86 

Length

Max length14
Median length13
Mean length11.540055
Min length9

Characters and Unicode

Total characters16710
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4 à 10 ans
2nd rowPlus de 20 ans
3rd row11 à 20 ans
4th rowPlus de 20 ans
5th rowPlus de 20 ans

Common Values

ValueCountFrequency (%)
Plus de 20 ans 466
32.2%
4 à 10 ans 352
24.3%
11 à 20 ans 326
22.5%
1 à 3 ans 218
15.1%
Moins d’un an 86
 
5.9%

Length

2023-06-18T04:19:07.979501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:08.253955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ans 1362
23.9%
à 896
15.7%
20 792
13.9%
plus 466
 
8.2%
de 466
 
8.2%
4 352
 
6.2%
10 352
 
6.2%
11 326
 
5.7%
1 218
 
3.8%
3 218
 
3.8%
Other values (3) 258
 
4.5%

Most occurring characters

ValueCountFrequency (%)
4258
25.5%
s 1914
11.5%
n 1620
 
9.7%
a 1448
 
8.7%
1 1222
 
7.3%
0 1144
 
6.8%
à 896
 
5.4%
2 792
 
4.7%
u 552
 
3.3%
d 552
 
3.3%
Other values (9) 2312
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8086
48.4%
Space Separator 4258
25.5%
Decimal Number 3728
22.3%
Uppercase Letter 552
 
3.3%
Final Punctuation 86
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1914
23.7%
n 1620
20.0%
a 1448
17.9%
à 896
11.1%
u 552
 
6.8%
d 552
 
6.8%
l 466
 
5.8%
e 466
 
5.8%
o 86
 
1.1%
i 86
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 1222
32.8%
0 1144
30.7%
2 792
21.2%
4 352
 
9.4%
3 218
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
P 466
84.4%
M 86
 
15.6%
Space Separator
ValueCountFrequency (%)
4258
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8638
51.7%
Common 8072
48.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1914
22.2%
n 1620
18.8%
a 1448
16.8%
à 896
10.4%
u 552
 
6.4%
d 552
 
6.4%
P 466
 
5.4%
l 466
 
5.4%
e 466
 
5.4%
M 86
 
1.0%
Other values (2) 172
 
2.0%
Common
ValueCountFrequency (%)
4258
52.8%
1 1222
 
15.1%
0 1144
 
14.2%
2 792
 
9.8%
4 352
 
4.4%
3 218
 
2.7%
’ 86
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15728
94.1%
None 896
 
5.4%
Punctuation 86
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4258
27.1%
s 1914
12.2%
n 1620
 
10.3%
a 1448
 
9.2%
1 1222
 
7.8%
0 1144
 
7.3%
2 792
 
5.0%
u 552
 
3.5%
d 552
 
3.5%
P 466
 
3.0%
Other values (7) 1760
11.2%
None
ValueCountFrequency (%)
à 896
100.0%
Punctuation
ValueCountFrequency (%)
’ 86
100.0%

profil_q27
Categorical

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size148.3 KiB
25 à 34 ans
502 
15 à 24 ans
317 
35 à 44 ans
305 
45 à 54 ans
168 
55 à 64 ans
118 
Other values (3)
 
38

Length

Max length15
Median length11
Mean length11.020718
Min length11

Characters and Unicode

Total characters15958
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15 à 24 ans
2nd row45 à 54 ans
3rd row25 à 34 ans
4th row25 à 34 ans
5th row55 à 64 ans

Common Values

ValueCountFrequency (%)
25 à 34 ans 502
34.7%
15 à 24 ans 317
21.9%
35 à 44 ans 305
21.1%
45 à 54 ans 168
 
11.6%
55 à 64 ans 118
 
8.1%
65 à 74 ans 30
 
2.1%
Moins de 15 ans 6
 
0.4%
75 ans et plus 2
 
0.1%

Length

2023-06-18T04:19:08.527918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:08.854542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
ans 1448
25.0%
à 1440
24.9%
25 502
 
8.7%
34 502
 
8.7%
15 323
 
5.6%
24 317
 
5.5%
35 305
 
5.3%
44 305
 
5.3%
54 168
 
2.9%
45 168
 
2.9%
Other values (9) 314
 
5.4%

Most occurring characters

ValueCountFrequency (%)
4344
27.2%
4 1913
12.0%
5 1734
 
10.9%
s 1456
 
9.1%
n 1454
 
9.1%
a 1448
 
9.1%
à 1440
 
9.0%
2 819
 
5.1%
3 807
 
5.1%
1 323
 
2.0%
Other values (11) 220
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5832
36.5%
Decimal Number 5776
36.2%
Space Separator 4344
27.2%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 1456
25.0%
n 1454
24.9%
a 1448
24.8%
à 1440
24.7%
e 8
 
0.1%
o 6
 
0.1%
i 6
 
0.1%
d 6
 
0.1%
t 2
 
< 0.1%
p 2
 
< 0.1%
Other values (2) 4
 
0.1%
Decimal Number
ValueCountFrequency (%)
4 1913
33.1%
5 1734
30.0%
2 819
14.2%
3 807
14.0%
1 323
 
5.6%
6 148
 
2.6%
7 32
 
0.6%
Space Separator
ValueCountFrequency (%)
4344
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10120
63.4%
Latin 5838
36.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 1456
24.9%
n 1454
24.9%
a 1448
24.8%
à 1440
24.7%
e 8
 
0.1%
M 6
 
0.1%
o 6
 
0.1%
i 6
 
0.1%
d 6
 
0.1%
t 2
 
< 0.1%
Other values (3) 6
 
0.1%
Common
ValueCountFrequency (%)
4344
42.9%
4 1913
18.9%
5 1734
 
17.1%
2 819
 
8.1%
3 807
 
8.0%
1 323
 
3.2%
6 148
 
1.5%
7 32
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14518
91.0%
None 1440
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4344
29.9%
4 1913
13.2%
5 1734
 
11.9%
s 1456
 
10.0%
n 1454
 
10.0%
a 1448
 
10.0%
2 819
 
5.6%
3 807
 
5.6%
1 323
 
2.2%
6 148
 
1.0%
Other values (10) 72
 
0.5%
None
ValueCountFrequency (%)
à 1440
100.0%

profil_q28
Categorical

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size94.3 KiB
Homme
762 
Femme
441 
Non-binaire
100 
Genderqueer ou non-conforme dans le genre
 
59
Identité différente 
 
42
Other values (2)
 
44

Length

Max length41
Median length5
Mean length8.2279006
Min length5

Characters and Unicode

Total characters11914
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon-binaire
2nd rowFemme
3rd rowFemme
4th rowFemme
5th rowHomme

Common Values

ValueCountFrequency (%)
Homme 762
52.6%
Femme 441
30.5%
Non-binaire 100
 
6.9%
Genderqueer ou non-conforme dans le genre 59
 
4.1%
Identité différente  42
 
2.9%
Genderfluid ou fluide dans le genre 38
 
2.6%
Personne bispirituelle (Two-Spirit) 6
 
0.4%

Length

2023-06-18T04:19:09.152972image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:09.457507image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
homme 762
38.3%
femme 441
22.2%
non-binaire 100
 
5.0%
ou 97
 
4.9%
dans 97
 
4.9%
le 97
 
4.9%
genre 97
 
4.9%
genderqueer 59
 
3.0%
non-conforme 59
 
3.0%
identité 42
 
2.1%
Other values (6) 136
 
6.8%

Most occurring characters

ValueCountFrequency (%)
e 2594
21.8%
m 2465
20.7%
o 1148
9.6%
n 764
 
6.4%
H 762
 
6.4%
539
 
4.5%
r 472
 
4.0%
F 441
 
3.7%
i 390
 
3.3%
d 354
 
3.0%
Other values (23) 1985
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9696
81.4%
Uppercase Letter 1460
 
12.3%
Space Separator 581
 
4.9%
Dash Punctuation 165
 
1.4%
Open Punctuation 6
 
0.1%
Close Punctuation 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2594
26.8%
m 2465
25.4%
o 1148
11.8%
n 764
 
7.9%
r 472
 
4.9%
i 390
 
4.0%
d 354
 
3.7%
u 238
 
2.5%
f 219
 
2.3%
a 197
 
2.0%
Other values (10) 855
 
8.8%
Uppercase Letter
ValueCountFrequency (%)
H 762
52.2%
F 441
30.2%
N 100
 
6.8%
G 97
 
6.6%
I 42
 
2.9%
P 6
 
0.4%
T 6
 
0.4%
S 6
 
0.4%
Space Separator
ValueCountFrequency (%)
539
92.8%
  42
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
- 165
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11156
93.6%
Common 758
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2594
23.3%
m 2465
22.1%
o 1148
10.3%
n 764
 
6.8%
H 762
 
6.8%
r 472
 
4.2%
F 441
 
4.0%
i 390
 
3.5%
d 354
 
3.2%
u 238
 
2.1%
Other values (18) 1528
13.7%
Common
ValueCountFrequency (%)
539
71.1%
- 165
 
21.8%
  42
 
5.5%
( 6
 
0.8%
) 6
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11788
98.9%
None 126
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2594
22.0%
m 2465
20.9%
o 1148
9.7%
n 764
 
6.5%
H 762
 
6.5%
539
 
4.6%
r 472
 
4.0%
F 441
 
3.7%
i 390
 
3.3%
d 354
 
3.0%
Other values (21) 1859
15.8%
None
ValueCountFrequency (%)
é 84
66.7%
  42
33.3%

profil_q29
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size89.5 KiB
Non
1222 
Oui
166 
Je préfère ne pas répondre
 
60

Length

Max length26
Median length3
Mean length3.9530387
Min length3

Characters and Unicode

Total characters5724
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOui
2nd rowOui
3rd rowJe préfère ne pas répondre
4th rowOui
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1222
84.4%
Oui 166
 
11.5%
Je préfère ne pas répondre 60
 
4.1%

Length

2023-06-18T04:19:09.732827image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:09.987930image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1222
72.4%
oui 166
 
9.8%
je 60
 
3.6%
préfère 60
 
3.6%
ne 60
 
3.6%
pas 60
 
3.6%
répondre 60
 
3.6%

Most occurring characters

ValueCountFrequency (%)
n 1342
23.4%
o 1282
22.4%
N 1222
21.3%
e 240
 
4.2%
r 240
 
4.2%
240
 
4.2%
p 180
 
3.1%
i 166
 
2.9%
u 166
 
2.9%
O 166
 
2.9%
Other values (7) 480
 
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4036
70.5%
Uppercase Letter 1448
 
25.3%
Space Separator 240
 
4.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1342
33.3%
o 1282
31.8%
e 240
 
5.9%
r 240
 
5.9%
p 180
 
4.5%
i 166
 
4.1%
u 166
 
4.1%
é 120
 
3.0%
f 60
 
1.5%
è 60
 
1.5%
Other values (3) 180
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
N 1222
84.4%
O 166
 
11.5%
J 60
 
4.1%
Space Separator
ValueCountFrequency (%)
240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5484
95.8%
Common 240
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1342
24.5%
o 1282
23.4%
N 1222
22.3%
e 240
 
4.4%
r 240
 
4.4%
p 180
 
3.3%
i 166
 
3.0%
u 166
 
3.0%
O 166
 
3.0%
é 120
 
2.2%
Other values (6) 360
 
6.6%
Common
ValueCountFrequency (%)
240
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5544
96.9%
None 180
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1342
24.2%
o 1282
23.1%
N 1222
22.0%
e 240
 
4.3%
r 240
 
4.3%
240
 
4.3%
p 180
 
3.2%
i 166
 
3.0%
u 166
 
3.0%
O 166
 
3.0%
Other values (5) 300
 
5.4%
None
ValueCountFrequency (%)
é 120
66.7%
è 60
33.3%

profil_q30
Categorical

Distinct10
Distinct (%)0.7%
Missing3
Missing (%)0.2%
Memory size93.1 KiB
Gaie
693 
Lesbienne
231 
Bisexuelle
163 
Queer
122 
Pansexuelle
116 
Other values (5)
120 

Length

Max length26
Median length17
Mean length6.9709343
Min length4

Characters and Unicode

Total characters10073
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowQueer
2nd rowLesbienne
3rd rowBisexuelle
4th rowLesbienne
5th rowGaie

Common Values

ValueCountFrequency (%)
Gaie 693
47.9%
Lesbienne 231
 
16.0%
Bisexuelle 163
 
11.3%
Queer 122
 
8.4%
Pansexuelle 116
 
8.0%
Autre 38
 
2.6%
Je préfère ne pas répondre 31
 
2.1%
Hétérosexuelle 25
 
1.7%
Asexuelle 15
 
1.0%
En questionnement 11
 
0.8%
(Missing) 3
 
0.2%

Length

2023-06-18T04:19:10.211725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:10.515312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
gaie 693
43.9%
lesbienne 231
 
14.6%
bisexuelle 163
 
10.3%
queer 122
 
7.7%
pansexuelle 116
 
7.3%
autre 38
 
2.4%
je 31
 
2.0%
préfère 31
 
2.0%
ne 31
 
2.0%
pas 31
 
2.0%
Other values (5) 93
 
5.9%

Most occurring characters

ValueCountFrequency (%)
e 2782
27.6%
i 1098
 
10.9%
a 840
 
8.3%
G 693
 
6.9%
n 684
 
6.8%
l 638
 
6.3%
s 592
 
5.9%
u 490
 
4.9%
x 319
 
3.2%
r 309
 
3.1%
Other values (19) 1628
16.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8455
83.9%
Uppercase Letter 1445
 
14.3%
Space Separator 173
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2782
32.9%
i 1098
 
13.0%
a 840
 
9.9%
n 684
 
8.1%
l 638
 
7.5%
s 592
 
7.0%
u 490
 
5.8%
x 319
 
3.8%
r 309
 
3.7%
b 231
 
2.7%
Other values (9) 472
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
G 693
48.0%
L 231
 
16.0%
B 163
 
11.3%
Q 122
 
8.4%
P 116
 
8.0%
A 53
 
3.7%
J 31
 
2.1%
H 25
 
1.7%
E 11
 
0.8%
Space Separator
ValueCountFrequency (%)
173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9900
98.3%
Common 173
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2782
28.1%
i 1098
 
11.1%
a 840
 
8.5%
G 693
 
7.0%
n 684
 
6.9%
l 638
 
6.4%
s 592
 
6.0%
u 490
 
4.9%
x 319
 
3.2%
r 309
 
3.1%
Other values (18) 1455
14.7%
Common
ValueCountFrequency (%)
173
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9930
98.6%
None 143
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2782
28.0%
i 1098
 
11.1%
a 840
 
8.5%
G 693
 
7.0%
n 684
 
6.9%
l 638
 
6.4%
s 592
 
6.0%
u 490
 
4.9%
x 319
 
3.2%
r 309
 
3.1%
Other values (17) 1485
15.0%
None
ValueCountFrequency (%)
é 112
78.3%
è 31
 
21.7%

profil_q31
Categorical

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size148.3 KiB
Universitaire - 1er cycle
521 
Universitaire - cycles supérieurs
448 
Collégial
299 
Secondaire
160 
Primaire
 
20

Length

Max length33
Median length25
Mean length22.279006
Min length8

Characters and Unicode

Total characters32260
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUniversitaire - 1er cycle
2nd rowCollégial
3rd rowUniversitaire - 1er cycle
4th rowUniversitaire - 1er cycle
5th rowUniversitaire - 1er cycle

Common Values

ValueCountFrequency (%)
Universitaire - 1er cycle 521
36.0%
Universitaire - cycles supérieurs 448
30.9%
Collégial 299
20.6%
Secondaire 160
 
11.0%
Primaire 20
 
1.4%

Length

2023-06-18T04:19:10.823676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:11.093620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
universitaire 969
22.3%
969
22.3%
1er 521
12.0%
cycle 521
12.0%
cycles 448
10.3%
supérieurs 448
10.3%
collégial 299
 
6.9%
secondaire 160
 
3.7%
primaire 20
 
0.5%

Most occurring characters

ValueCountFrequency (%)
e 4216
13.1%
i 3854
11.9%
r 3555
11.0%
2907
 
9.0%
s 2313
 
7.2%
c 2098
 
6.5%
l 1866
 
5.8%
a 1448
 
4.5%
n 1129
 
3.5%
y 969
 
3.0%
Other values (15) 7905
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26415
81.9%
Space Separator 2907
 
9.0%
Uppercase Letter 1448
 
4.5%
Dash Punctuation 969
 
3.0%
Decimal Number 521
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4216
16.0%
i 3854
14.6%
r 3555
13.5%
s 2313
8.8%
c 2098
7.9%
l 1866
7.1%
a 1448
 
5.5%
n 1129
 
4.3%
y 969
 
3.7%
t 969
 
3.7%
Other values (8) 3998
15.1%
Uppercase Letter
ValueCountFrequency (%)
U 969
66.9%
C 299
 
20.6%
S 160
 
11.0%
P 20
 
1.4%
Space Separator
ValueCountFrequency (%)
2907
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 969
100.0%
Decimal Number
ValueCountFrequency (%)
1 521
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27863
86.4%
Common 4397
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4216
15.1%
i 3854
13.8%
r 3555
12.8%
s 2313
8.3%
c 2098
 
7.5%
l 1866
 
6.7%
a 1448
 
5.2%
n 1129
 
4.1%
y 969
 
3.5%
U 969
 
3.5%
Other values (12) 5446
19.5%
Common
ValueCountFrequency (%)
2907
66.1%
- 969
 
22.0%
1 521
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31513
97.7%
None 747
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4216
13.4%
i 3854
12.2%
r 3555
11.3%
2907
9.2%
s 2313
 
7.3%
c 2098
 
6.7%
l 1866
 
5.9%
a 1448
 
4.6%
n 1129
 
3.6%
y 969
 
3.1%
Other values (14) 7158
22.7%
None
ValueCountFrequency (%)
é 747
100.0%

profil_q32
Categorical

Distinct20
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size132.1 KiB
Français
1113 
Anglais
277 
Espagnol
 
22
Portugais
 
9
Arabe
 
6
Other values (15)
 
21

Length

Max length45
Median length9
Mean length8.9834254
Min length5

Characters and Unicode

Total characters13008
Distinct characters42
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)0.7%

Sample

1st rowAnglais
2nd rowFrançais
3rd rowAnglais
4th rowAnglais
5th rowFrançais

Common Values

ValueCountFrequency (%)
Français 1113
76.9%
Anglais 277
 
19.1%
Espagnol 22
 
1.5%
Portugais 9
 
0.6%
Arabe 6
 
0.4%
Russe 3
 
0.2%
Italien 2
 
0.1%
Vietnamien 2
 
0.1%
Grec 2
 
0.1%
Autre (veuillez préciser) Bulgare 2
 
0.1%
Other values (10) 10
 
0.7%

Length

2023-06-18T04:19:11.378449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
français 1113
75.1%
anglais 277
 
18.7%
espagnol 22
 
1.5%
autre 10
 
0.7%
préciser 10
 
0.7%
veuillez 10
 
0.7%
portugais 9
 
0.6%
arabe 6
 
0.4%
russe 3
 
0.2%
italien 2
 
0.1%
Other values (18) 21
 
1.4%

Most occurring characters

ValueCountFrequency (%)
a 2561
19.7%
1473
11.3%
s 1444
11.1%
i 1433
11.0%
n 1429
11.0%
r 1168
9.0%
F 1116
8.6%
ç 1114
8.6%
l 330
 
2.5%
g 317
 
2.4%
Other values (32) 623
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10050
77.3%
Space Separator 1473
 
11.3%
Uppercase Letter 1462
 
11.2%
Open Punctuation 11
 
0.1%
Close Punctuation 11
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2561
25.5%
s 1444
14.4%
i 1433
14.3%
n 1429
14.2%
r 1168
11.6%
ç 1114
11.1%
l 330
 
3.3%
g 317
 
3.2%
e 65
 
0.6%
u 39
 
0.4%
Other values (13) 150
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
F 1116
76.3%
A 294
 
20.1%
E 22
 
1.5%
P 9
 
0.6%
R 4
 
0.3%
B 3
 
0.2%
L 2
 
0.1%
S 2
 
0.1%
V 2
 
0.1%
G 2
 
0.1%
Other values (5) 6
 
0.4%
Space Separator
ValueCountFrequency (%)
1473
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11512
88.5%
Common 1496
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2561
22.2%
s 1444
12.5%
i 1433
12.4%
n 1429
12.4%
r 1168
10.1%
F 1116
9.7%
ç 1114
9.7%
l 330
 
2.9%
g 317
 
2.8%
A 294
 
2.6%
Other values (28) 306
 
2.7%
Common
ValueCountFrequency (%)
1473
98.5%
( 11
 
0.7%
) 11
 
0.7%
/ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11883
91.4%
None 1125
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2561
21.6%
1473
12.4%
s 1444
12.2%
i 1433
12.1%
n 1429
12.0%
r 1168
9.8%
F 1116
9.4%
l 330
 
2.8%
g 317
 
2.7%
A 294
 
2.5%
Other values (30) 318
 
2.7%
None
ValueCountFrequency (%)
ç 1114
99.0%
é 11
 
1.0%

profil_q33
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
1202 
Oui
246 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowOui
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1202
83.0%
Oui 246
 
17.0%

Length

2023-06-18T04:19:11.658149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:11.914957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1202
83.0%
oui 246
 
17.0%

Most occurring characters

ValueCountFrequency (%)
N 1202
27.7%
o 1202
27.7%
n 1202
27.7%
O 246
 
5.7%
u 246
 
5.7%
i 246
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1202
41.5%
n 1202
41.5%
u 246
 
8.5%
i 246
 
8.5%
Uppercase Letter
ValueCountFrequency (%)
N 1202
83.0%
O 246
 
17.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1202
27.7%
o 1202
27.7%
n 1202
27.7%
O 246
 
5.7%
u 246
 
5.7%
i 246
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1202
27.7%
o 1202
27.7%
n 1202
27.7%
O 246
 
5.7%
u 246
 
5.7%
i 246
 
5.7%

profil_q34
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
1186 
Oui
262 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowOui
4th rowOui
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1186
81.9%
Oui 262
 
18.1%

Length

2023-06-18T04:19:12.123557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:12.429122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1186
81.9%
oui 262
 
18.1%

Most occurring characters

ValueCountFrequency (%)
N 1186
27.3%
o 1186
27.3%
n 1186
27.3%
O 262
 
6.0%
u 262
 
6.0%
i 262
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1186
41.0%
n 1186
41.0%
u 262
 
9.0%
i 262
 
9.0%
Uppercase Letter
ValueCountFrequency (%)
N 1186
81.9%
O 262
 
18.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1186
27.3%
o 1186
27.3%
n 1186
27.3%
O 262
 
6.0%
u 262
 
6.0%
i 262
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1186
27.3%
o 1186
27.3%
n 1186
27.3%
O 262
 
6.0%
u 262
 
6.0%
i 262
 
6.0%

profil_q35
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
1393 
Oui
 
55

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 1393
96.2%
Oui 55
 
3.8%

Length

2023-06-18T04:19:12.700550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:13.115652image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 1393
96.2%
oui 55
 
3.8%

Most occurring characters

ValueCountFrequency (%)
N 1393
32.1%
o 1393
32.1%
n 1393
32.1%
O 55
 
1.3%
u 55
 
1.3%
i 55
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1393
48.1%
n 1393
48.1%
u 55
 
1.9%
i 55
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
N 1393
96.2%
O 55
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1393
32.1%
o 1393
32.1%
n 1393
32.1%
O 55
 
1.3%
u 55
 
1.3%
i 55
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1393
32.1%
o 1393
32.1%
n 1393
32.1%
O 55
 
1.3%
u 55
 
1.3%
i 55
 
1.3%

profil_q36
Text

Distinct279
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size93.3 KiB
2023-06-18T04:19:13.696846image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length28
Median length3
Mean length4.3515193
Min length3

Characters and Unicode

Total characters6301
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)8.3%

Sample

1st rowH2J
2nd rowH3K
3rd rowH2K
4th rowJe n’ai pas de domicile fixe
5th rowH1V
ValueCountFrequency (%)
h2l 116
 
6.3%
h2k 104
 
5.7%
h1w 90
 
4.9%
fixe 78
 
4.2%
je 78
 
4.2%
domicile 78
 
4.2%
de 78
 
4.2%
pas 78
 
4.2%
n’ai 78
 
4.2%
h2s 55
 
3.0%
Other values (145) 1005
54.7%
2023-06-18T04:19:14.801687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
H 1143
18.1%
2 600
 
9.5%
390
 
6.2%
1 350
 
5.6%
e 333
 
5.3%
i 312
 
5.0%
h 225
 
3.6%
3 178
 
2.8%
J 172
 
2.7%
a 169
 
2.7%
Other values (46) 2429
38.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2350
37.3%
Uppercase Letter 2098
33.3%
Decimal Number 1385
22.0%
Space Separator 390
 
6.2%
Final Punctuation 78
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 333
14.2%
i 312
13.3%
h 225
 
9.6%
a 169
 
7.2%
d 156
 
6.6%
l 130
 
5.5%
s 103
 
4.4%
c 102
 
4.3%
x 102
 
4.3%
p 93
 
4.0%
Other values (14) 625
26.6%
Uppercase Letter
ValueCountFrequency (%)
H 1143
54.5%
J 172
 
8.2%
L 96
 
4.6%
W 83
 
4.0%
K 70
 
3.3%
G 64
 
3.1%
S 62
 
3.0%
V 51
 
2.4%
T 46
 
2.2%
R 41
 
2.0%
Other values (10) 270
 
12.9%
Decimal Number
ValueCountFrequency (%)
2 600
43.3%
1 350
25.3%
3 178
 
12.9%
4 164
 
11.8%
9 24
 
1.7%
8 22
 
1.6%
7 21
 
1.5%
0 11
 
0.8%
5 8
 
0.6%
6 7
 
0.5%
Space Separator
ValueCountFrequency (%)
390
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4448
70.6%
Common 1853
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 1143
25.7%
e 333
 
7.5%
i 312
 
7.0%
h 225
 
5.1%
J 172
 
3.9%
a 169
 
3.8%
d 156
 
3.5%
l 130
 
2.9%
s 103
 
2.3%
c 102
 
2.3%
Other values (34) 1603
36.0%
Common
ValueCountFrequency (%)
2 600
32.4%
390
21.0%
1 350
18.9%
3 178
 
9.6%
4 164
 
8.9%
’ 78
 
4.2%
9 24
 
1.3%
8 22
 
1.2%
7 21
 
1.1%
0 11
 
0.6%
Other values (2) 15
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6223
98.8%
Punctuation 78
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 1143
18.4%
2 600
 
9.6%
390
 
6.3%
1 350
 
5.6%
e 333
 
5.4%
i 312
 
5.0%
h 225
 
3.6%
3 178
 
2.9%
J 172
 
2.8%
a 169
 
2.7%
Other values (45) 2351
37.8%
Punctuation
ValueCountFrequency (%)
’ 78
100.0%

profil_q37
Categorical

Distinct12
Distinct (%)0.8%
Missing16
Missing (%)1.1%
Memory size162.6 KiB
60 000 $ à 79 999 $
194 
100 000 $ à 149,999 $
193 
80 000 $ à 99 999 $
170 
50 000 $ à 59 999 $
128 
150 000 $ et plus
125 
Other values (7)
622 

Length

Max length21
Median length19
Mean length18.914804
Min length16

Characters and Unicode

Total characters27086
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row80 000 $ à 99 999 $
2nd row15 000 $ à 19 999 $
3rd row60 000 $ à 79 999 $
4th row10 000 $ à 14 999 $
5th row100 000 $ à 149,999 $

Common Values

ValueCountFrequency (%)
60 000 $ à 79 999 $ 194
13.4%
100 000 $ à 149,999 $ 193
13.3%
80 000 $ à 99 999 $ 170
11.7%
50 000 $ à 59 999 $ 128
8.8%
150 000 $ et plus 125
8.6%
40 000 $ à 49 999 $ 124
8.6%
20 000 $ à 29 999 $ 122
8.4%
30 000 $ à 39 999 $ 110
7.6%
10 000 $ à 14 999 $ 88
6.1%
15 000 $ à 19 999 $ 72
 
5.0%
Other values (2) 106
7.3%

Length

2023-06-18T04:19:15.329881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2693
28.4%
000 1432
15.1%
à 1261
13.3%
999 1068
 
11.3%
60 194
 
2.0%
79 194
 
2.0%
100 193
 
2.0%
149,999 193
 
2.0%
80 170
 
1.8%
99 170
 
1.8%
Other values (19) 1921
20.2%

Most occurring characters

ValueCountFrequency (%)
8057
29.7%
0 5743
21.2%
9 5126
18.9%
$ 2693
 
9.9%
à 1261
 
4.7%
1 831
 
3.1%
5 559
 
2.1%
4 529
 
2.0%
2 244
 
0.9%
3 220
 
0.8%
Other values (15) 1823
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13810
51.0%
Space Separator 8057
29.7%
Currency Symbol 2693
 
9.9%
Lowercase Letter 2287
 
8.4%
Other Punctuation 193
 
0.7%
Uppercase Letter 46
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
à 1261
55.1%
s 171
 
7.5%
e 171
 
7.5%
l 125
 
5.5%
u 125
 
5.5%
p 125
 
5.5%
t 125
 
5.5%
o 46
 
2.0%
i 46
 
2.0%
n 46
 
2.0%
Decimal Number
ValueCountFrequency (%)
0 5743
41.6%
9 5126
37.1%
1 831
 
6.0%
5 559
 
4.0%
4 529
 
3.8%
2 244
 
1.8%
3 220
 
1.6%
6 194
 
1.4%
7 194
 
1.4%
8 170
 
1.2%
Space Separator
ValueCountFrequency (%)
8057
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2693
100.0%
Other Punctuation
ValueCountFrequency (%)
, 193
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24753
91.4%
Latin 2333
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
8057
32.5%
0 5743
23.2%
9 5126
20.7%
$ 2693
 
10.9%
1 831
 
3.4%
5 559
 
2.3%
4 529
 
2.1%
2 244
 
1.0%
3 220
 
0.9%
6 194
 
0.8%
Other values (3) 557
 
2.3%
Latin
ValueCountFrequency (%)
à 1261
54.1%
s 171
 
7.3%
e 171
 
7.3%
l 125
 
5.4%
u 125
 
5.4%
p 125
 
5.4%
t 125
 
5.4%
M 46
 
2.0%
o 46
 
2.0%
i 46
 
2.0%
Other values (2) 92
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25825
95.3%
None 1261
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8057
31.2%
0 5743
22.2%
9 5126
19.8%
$ 2693
 
10.4%
1 831
 
3.2%
5 559
 
2.2%
4 529
 
2.0%
2 244
 
0.9%
3 220
 
0.9%
6 194
 
0.8%
Other values (14) 1629
 
6.3%
None
ValueCountFrequency (%)
à 1261
100.0%

interet_participer_groupe_discussion_q38
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size85.0 KiB
Non
901 
Oui
547 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters4344
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowNon
4th rowNon
5th rowOui

Common Values

ValueCountFrequency (%)
Non 901
62.2%
Oui 547
37.8%

Length

2023-06-18T04:19:15.778676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:16.028887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 901
62.2%
oui 547
37.8%

Most occurring characters

ValueCountFrequency (%)
N 901
20.7%
o 901
20.7%
n 901
20.7%
O 547
12.6%
u 547
12.6%
i 547
12.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2896
66.7%
Uppercase Letter 1448
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 901
31.1%
n 901
31.1%
u 547
18.9%
i 547
18.9%
Uppercase Letter
ValueCountFrequency (%)
N 901
62.2%
O 547
37.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 4344
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 901
20.7%
o 901
20.7%
n 901
20.7%
O 547
12.6%
u 547
12.6%
i 547
12.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 901
20.7%
o 901
20.7%
n 901
20.7%
O 547
12.6%
u 547
12.6%
i 547
12.6%

interet_participer_groupe_discussion_q40
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.4%
Missing898
Missing (%)62.0%
Memory size67.4 KiB
Non
507 
Oui
 
43

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1650
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNon
2nd rowNon
3rd rowNon
4th rowNon
5th rowNon

Common Values

ValueCountFrequency (%)
Non 507
35.0%
Oui 43
 
3.0%
(Missing) 898
62.0%

Length

2023-06-18T04:19:16.228499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-06-18T04:19:16.455454image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
non 507
92.2%
oui 43
 
7.8%

Most occurring characters

ValueCountFrequency (%)
N 507
30.7%
o 507
30.7%
n 507
30.7%
O 43
 
2.6%
u 43
 
2.6%
i 43
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1100
66.7%
Uppercase Letter 550
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 507
46.1%
n 507
46.1%
u 43
 
3.9%
i 43
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
N 507
92.2%
O 43
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 1650
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 507
30.7%
o 507
30.7%
n 507
30.7%
O 43
 
2.6%
u 43
 
2.6%
i 43
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 507
30.7%
o 507
30.7%
n 507
30.7%
O 43
 
2.6%
u 43
 
2.6%
i 43
 
2.6%

Interactions

2023-06-18T04:17:50.483468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:20.412505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:23.896836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:27.090187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:29.650337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:32.408474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:34.998529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:38.254302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:41.432900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:44.233875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:47.808234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:50.864501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:20.672911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:24.292727image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:27.346886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:29.915777image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:32.681538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:35.243922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:38.656977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:41.974517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:44.478638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:48.054809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:51.253257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:20.900861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:24.556083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:27.571745image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:30.132751image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:32.911028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:35.483052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:38.991551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:42.199063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:44.711045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:48.268298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:51.617963image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:21.155002image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:24.922680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:27.801411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:30.371242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:33.138511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:35.728226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:39.283666image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:42.414301image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:44.951415image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:48.479803image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:51.988592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:21.395327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:25.267779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:28.047955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:30.811666image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:33.354264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:35.961080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:39.676149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:42.633646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:45.308662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:48.699996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:52.355490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:21.834989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:25.628423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:28.272825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:31.032059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:33.595501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:36.219708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:40.047396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:42.867421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:45.736880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:48.959460image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:52.709120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:22.102584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:25.993044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:28.492509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:31.247772image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:33.826887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:36.544964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:40.288585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:43.098063image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:46.132589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:49.183678image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:53.097646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:22.455853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:26.206233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:28.730994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:31.480591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:34.056552image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:36.884287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:40.517864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:43.322266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:46.538249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:49.421165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:53.462808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:22.797502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:26.432571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:28.968218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:31.740423image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:34.270763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:37.224467image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:40.763601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:43.536479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:46.978399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:49.640342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:53.783336image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:23.151513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:26.652475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:29.191721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:31.956358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:34.498631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:37.588484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:40.998139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:43.787316image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:47.356522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:49.892308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:54.059705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:23.519224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:26.868759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:29.427506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:32.180998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:34.738716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:37.912880image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:41.215543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:44.013785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:47.581700image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-18T04:17:50.162616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-06-18T04:19:16.752106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
idpiste_action_q22_1piste_action_q22_2piste_action_q22_3piste_action_q22_4piste_action_q22_5piste_action_q22_6piste_action_q22_7piste_action_q22_8piste_action_q22_9piste_action_q22_10acces_services _ Ville_q1acces_services _ Ville_q3acces_services _ Ville_q4acces_services _ Ville_q5acces_services _ Ville_q7_1acces_services _ Ville_q7_2acces_services _ Ville_q7_3acces_services _ Ville_q7_4acces_services _ Ville_q7_5acces_services _ Ville_q8_1acces_services _ Ville_q8_2acces_services _ Ville_q8_3acces_services _ Ville_q8_4acces_services _ Ville_q8_5acces_services _ Ville_q9milieu_et_qualite_de_vie_q11_1milieu_et_qualite_de_vie_q11_2milieu_et_qualite_de_vie_q11_3milieu_et_qualite_de_vie_q11_4milieu_et_qualite_de_vie_q11_5milieu_et_qualité_de_vie_q11_6milieu_et_qualite_de_vie_q11_7milieu_et_qualite_de_vie_q11_8milieu_et_qualite_de_vie_q12securité_dans_espace_public_q13securité_dans_espace_public_q16securité_dans_espace_public_q18participation_citoyenne_q19participation_citoyenne_q20profil_q25profil_q26profil_q27profil_q28profil_q29profil_q30profil_q31profil_q32profil_q33profil_q34profil_q35profil_q37interet_participer_groupe_discussion_q38interet_participer_groupe_discussion_q40
id1.000-0.045-0.022-0.002-0.006-0.008-0.012-0.0210.0520.078-0.0050.0970.0490.0370.0680.0690.0690.0980.0000.0440.0700.0000.0000.0350.0580.0000.0980.1030.0570.0570.0730.0670.0000.0000.0000.0180.0220.1680.0000.0000.2160.0300.0690.0790.1360.0660.0500.0530.0000.0000.0440.0000.0620.000
piste_action_q22_1-0.0451.0000.0090.0730.131-0.025-0.160-0.153-0.246-0.274-0.3450.0420.0000.0000.0570.0410.0000.0580.0240.0000.0590.0330.0480.0490.0330.0250.0780.0000.0000.0000.0330.0380.0030.0000.0000.0390.0470.0000.0000.0480.0590.0600.0200.0360.0640.0000.0260.0420.0000.0000.0000.0000.0000.131
piste_action_q22_2-0.0220.0091.000-0.113-0.015-0.077-0.171-0.274-0.304-0.078-0.1040.0290.0000.0480.0000.0000.0660.0360.0000.0000.0000.0000.0000.0000.0380.0250.0640.0000.0000.0330.0290.0050.0000.0000.0000.0000.0550.2740.0000.0000.0000.0100.0000.0410.0000.0000.0100.0000.0920.0170.0590.0160.0000.028
piste_action_q22_3-0.0020.073-0.1131.000-0.0010.073-0.077-0.016-0.180-0.245-0.2620.0510.0200.0110.0230.0000.0410.0090.0380.0350.0000.0330.0000.0000.0000.0400.0590.0540.0790.0330.0660.0420.0350.0540.0450.0290.0290.0000.0000.0890.0240.0000.0390.0440.0350.0180.0000.0380.0000.0000.0000.0060.0560.094
piste_action_q22_4-0.0060.131-0.015-0.0011.0000.038-0.172-0.157-0.224-0.181-0.2940.0000.0000.0300.0000.0490.0610.0000.0000.0500.0000.0000.0400.0000.0000.0000.0600.0510.0710.0760.0640.0750.0340.0230.1310.0000.0690.1440.0000.0000.0380.0550.0580.0700.0660.0500.0500.0490.0000.0000.0440.0420.0220.000
piste_action_q22_5-0.008-0.025-0.0770.0730.0381.000-0.128-0.048-0.180-0.198-0.2180.0900.0320.0390.0000.0000.0870.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0330.0470.0700.0550.0290.0370.0120.0830.0000.0430.0000.0000.0000.0000.0260.0000.0500.0520.0000.0220.0000.0680.0000.0840.0270.0490.030
piste_action_q22_6-0.012-0.160-0.171-0.077-0.172-0.1281.000-0.062-0.027-0.0520.0260.0830.0630.0200.0000.0000.0520.0370.0250.0700.0000.0000.0470.0050.0000.0000.0260.0430.0000.0360.0310.0370.0000.0560.0580.0610.0000.0000.0000.0000.0290.0340.0540.0260.0000.0330.0180.0140.0670.0470.0000.0330.0580.129
piste_action_q22_7-0.021-0.153-0.274-0.016-0.157-0.048-0.0621.0000.137-0.004-0.1660.0880.0230.0000.0400.0360.0000.0440.0550.0540.0090.0310.0000.0000.0630.0000.0000.0000.0000.0480.0280.0320.0000.0000.0570.0230.0000.0000.0000.0000.0000.0000.0000.0080.0000.0360.0000.0270.0000.0470.0000.0000.0000.016
piste_action_q22_80.052-0.246-0.304-0.180-0.224-0.180-0.0270.1371.0000.068-0.0050.0890.0660.0490.0000.0330.0000.0000.0000.0470.0300.0000.0000.0640.0460.0000.0000.0500.0000.0210.0000.0480.0000.0000.0690.0000.0000.0000.0350.0810.0520.0000.0180.0000.0550.0400.0510.0250.0870.0320.0000.0450.0640.106
piste_action_q22_90.078-0.274-0.078-0.245-0.181-0.198-0.052-0.0040.0681.0000.0350.0400.0320.0280.0610.0400.0000.0770.0000.0500.0000.0000.0000.0000.0140.0360.0480.0780.0500.0500.0510.0600.0350.0000.1060.0270.0000.0000.0480.2480.0440.0250.0060.0470.1150.0400.0000.0000.0000.0000.0410.0000.0810.114
piste_action_q22_10-0.005-0.345-0.104-0.262-0.294-0.2180.026-0.166-0.0050.0351.0000.0410.0000.0480.0170.0230.0000.0090.0460.0650.0360.0370.0000.0300.0000.0000.0700.0820.0790.0770.0590.0910.0250.0580.1150.0000.0000.2700.0210.0880.0260.0590.0410.0460.0000.0630.0560.0390.0670.0000.0000.0000.0710.046
acces_services _ Ville_q10.0970.0420.0290.0510.0000.0900.0830.0880.0890.0400.0411.0000.6990.1240.0000.0110.0440.0790.0000.0280.0720.1110.1000.0360.0000.0300.0670.0440.0380.1150.1050.0850.0330.0000.0000.0550.0000.0570.0870.0570.0650.0000.0000.0780.0000.0790.0440.0920.0490.0000.0000.0410.0820.062
acces_services _ Ville_q30.0490.0000.0000.0200.0000.0320.0630.0230.0660.0320.0000.6991.0000.0740.0370.0710.0920.1090.0240.0800.0790.1110.0880.0490.0550.0000.0000.0270.0300.0710.0610.0670.0000.0160.0460.0350.0000.1560.1390.0000.0370.0000.0420.0570.0360.0600.0470.0460.0000.0700.0380.0600.0770.104
acces_services _ Ville_q40.0370.0000.0480.0110.0300.0390.0200.0000.0490.0280.0480.1240.0741.0000.2000.1460.2090.2230.1430.1770.0900.1040.1170.1120.0820.1820.1530.1840.1940.1590.2180.1350.1670.1670.2070.1660.0850.0000.0390.2130.0510.0690.0660.0610.1120.0910.0470.0460.0950.1100.0510.0410.0980.000
acces_services _ Ville_q50.0680.0570.0000.0230.0000.0000.0000.0400.0000.0610.0170.0000.0370.2001.0000.1900.2170.2730.1560.2390.1550.1760.1730.1510.1320.3080.2600.2450.2300.2330.2360.1730.1780.2000.3650.2880.1140.2030.0280.3720.0850.0310.1210.2050.2910.1870.0670.1230.1120.1060.0660.1530.1420.105
acces_services _ Ville_q7_10.0690.0410.0000.0000.0490.0000.0000.0360.0330.0400.0230.0110.0710.1460.1901.0000.2870.2370.2620.4000.4390.1870.1270.1750.2890.1610.1830.2480.2800.1830.2300.1820.1590.1290.1990.1590.0000.0000.0000.1350.0930.0830.1500.0680.1230.1060.0470.0530.0380.0350.0000.1300.0640.072
acces_services _ Ville_q7_20.0690.0000.0660.0410.0610.0870.0520.0000.0000.0000.0000.0440.0920.2090.2170.2871.0000.4020.2440.2990.1990.3560.2110.1920.1960.2090.2070.2130.1930.2030.2360.1540.2370.2370.2100.2000.0710.0000.1140.2440.0540.0420.0450.1290.1130.1090.0520.0930.0900.1050.0000.1050.1310.027
acces_services _ Ville_q7_30.0980.0580.0360.0090.0000.0000.0370.0440.0000.0770.0090.0790.1090.2230.2730.2370.4021.0000.2560.2960.1360.2150.3880.1700.1440.2040.2240.2370.2110.2240.2350.1800.1660.1870.1900.1840.0860.2060.0800.1230.1130.0700.0810.1710.1900.1330.1110.1010.0890.1270.0320.1100.1210.118
acces_services _ Ville_q7_40.0000.0240.0000.0380.0000.0000.0250.0550.0000.0000.0460.0000.0240.1430.1560.2620.2440.2561.0000.3270.1300.1380.1220.3260.2010.1430.2920.1980.1980.1890.2070.1750.1510.1560.1530.1320.0130.0000.0520.0000.0940.1190.1030.1300.1080.1060.0560.0720.0270.0590.0000.0500.0800.083
acces_services _ Ville_q7_50.0440.0000.0000.0350.0500.0000.0700.0540.0470.0500.0650.0280.0800.1770.2390.4000.2990.2960.3271.0000.2650.1910.1540.1850.4330.2020.1990.2760.2300.2370.2520.1590.1770.1840.1680.1890.0950.1320.0660.1090.1210.0310.1510.1630.1780.1360.0460.1230.1500.1080.0150.1530.1120.059
acces_services _ Ville_q8_10.0700.0590.0000.0000.0000.0050.0000.0090.0300.0000.0360.0720.0790.0900.1550.4390.1990.1360.1300.2651.0000.3920.2950.3270.4520.1250.1140.1330.1290.1140.1400.1150.1050.0860.1140.1390.0940.0000.0350.1070.0400.0450.0690.0500.0580.0660.0320.0000.0750.0220.0000.1020.0000.053
acces_services _ Ville_q8_20.0000.0330.0000.0330.0000.0000.0000.0310.0000.0000.0370.1110.1110.1040.1760.1870.3560.2150.1380.1910.3921.0000.5160.4350.3750.1560.1580.1330.1120.1260.1280.0730.1170.1190.1610.1560.0800.0000.0130.0830.0330.0730.1060.1040.0920.1120.0890.0350.0730.0000.0260.0650.1030.056
acces_services _ Ville_q8_30.0000.0480.0000.0000.0400.0000.0470.0000.0000.0000.0000.1000.0880.1170.1730.1270.2110.3880.1220.1540.2950.5161.0000.4140.3360.1170.1380.1210.1080.1230.1210.0790.1010.0880.1520.1660.0800.0000.0000.1430.0230.0680.1150.1030.0860.0940.0990.0530.1170.0220.0000.0750.0670.088
acces_services _ Ville_q8_40.0350.0490.0000.0000.0000.0000.0050.0000.0640.0000.0300.0360.0490.1120.1510.1750.1920.1700.3260.1850.3270.4350.4141.0000.4430.1440.1750.1300.1220.1230.1170.1080.1000.0900.1500.1510.0710.0000.0470.0180.0000.1210.0870.1030.1030.1290.0400.0000.0640.0160.0000.0730.0580.043
acces_services _ Ville_q8_50.0580.0330.0380.0000.0000.0000.0000.0630.0460.0140.0000.0000.0550.0820.1320.2890.1960.1440.2010.4330.4520.3750.3360.4431.0000.1210.0910.1470.1280.1280.1260.0900.0780.0960.0990.1070.0330.0400.0000.0420.0690.0000.1010.0460.0930.0860.0630.0650.0850.0480.0000.0660.0070.000
acces_services _ Ville_q90.0000.0250.0250.0400.0000.0000.0000.0000.0000.0360.0000.0300.0000.1820.3080.1610.2090.2040.1430.2020.1250.1560.1170.1440.1211.0000.2210.2040.1840.1800.2140.1540.1770.1720.2960.2700.0900.0000.0000.2170.0000.0110.1260.1120.1870.1090.0700.0000.0720.0650.0560.1060.0580.118
milieu_et_qualite_de_vie_q11_10.0980.0780.0640.0590.0600.0000.0260.0000.0000.0480.0700.0670.0000.1530.2600.1830.2070.2240.2920.1990.1140.1580.1380.1750.0910.2211.0000.4240.3880.3760.4030.3140.2870.3130.3700.1930.0630.0000.0470.1540.0910.0000.0570.2110.1910.1990.0000.1040.0800.1080.0490.0920.1140.137
milieu_et_qualite_de_vie_q11_20.1030.0000.0000.0540.0510.0330.0430.0000.0500.0780.0820.0440.0270.1840.2450.2480.2130.2370.1980.2760.1330.1330.1210.1300.1470.2040.4241.0000.7020.4780.5230.4480.2870.2950.3280.1690.0530.0000.0000.0620.0720.0420.0670.1100.1990.1590.0330.1310.0790.1130.0000.0790.1510.065
milieu_et_qualite_de_vie_q11_30.0570.0000.0000.0790.0710.0470.0000.0000.0000.0500.0790.0380.0300.1940.2300.2800.1930.2110.1980.2300.1290.1120.1080.1220.1280.1840.3880.7021.0000.4780.5270.4590.2730.2780.3120.1830.0180.1120.0000.0510.0630.0660.0430.1150.1820.1520.0000.1160.0000.0000.0000.1080.1530.039
milieu_et_qualite_de_vie_q11_40.0570.0000.0330.0330.0760.0700.0360.0480.0210.0500.0770.1150.0710.1590.2330.1830.2030.2240.1890.2370.1140.1260.1230.1230.1280.1800.3760.4780.4781.0000.5420.4880.2640.2930.3220.1770.0590.0000.0000.0000.0820.0510.0680.1490.1770.1760.0260.1270.0890.1170.0000.1080.1600.154
milieu_et_qualite_de_vie_q11_50.0730.0330.0290.0660.0640.0550.0310.0280.0000.0510.0590.1050.0610.2180.2360.2300.2360.2350.2070.2520.1400.1280.1210.1170.1260.2140.4030.5230.5270.5421.0000.5110.3050.3150.3100.1870.0410.0970.0000.1220.0790.0000.0310.1320.1670.1450.0000.1110.0730.0850.0000.1000.1540.163
milieu_et_qualité_de_vie_q11_60.0670.0380.0050.0420.0750.0290.0370.0320.0480.0600.0910.0850.0670.1350.1730.1820.1540.1800.1750.1590.1150.0730.0790.1080.0900.1540.3140.4480.4590.4880.5111.0000.2700.2710.2710.1560.0840.0000.0610.0680.0760.0420.0430.0950.1480.1420.0490.0840.0000.0000.0000.1060.1590.085
milieu_et_qualite_de_vie_q11_70.0000.0030.0000.0350.0340.0370.0000.0000.0000.0350.0250.0330.0000.1670.1780.1590.2370.1660.1510.1770.1050.1170.1010.1000.0780.1770.2870.2870.2730.2640.3050.2701.0000.6010.3640.1640.0770.1140.0630.1340.0560.0190.0160.0750.0660.0950.0330.0000.0540.0740.0680.0590.1020.092
milieu_et_qualite_de_vie_q11_80.0000.0000.0000.0540.0230.0120.0560.0000.0000.0000.0580.0000.0160.1670.2000.1290.2370.1870.1560.1840.0860.1190.0880.0900.0960.1720.3130.2950.2780.2930.3150.2710.6011.0000.3490.1390.0580.0850.0650.1640.0460.0000.0260.1160.0890.1280.0000.0000.0490.1050.0560.0780.0950.061
milieu_et_qualite_de_vie_q120.0000.0000.0000.0450.1310.0830.0580.0570.0690.1060.1150.0000.0460.2070.3650.1990.2100.1900.1530.1680.1140.1610.1520.1500.0990.2960.3700.3280.3120.3220.3100.2710.3640.3491.0000.3750.0000.0000.0080.0000.1430.0000.1400.2890.1260.2870.0450.0420.0140.0000.0320.1610.0830.106
securité_dans_espace_public_q130.0180.0390.0000.0290.0000.0000.0610.0230.0000.0270.0000.0550.0350.1660.2880.1590.2000.1840.1320.1890.1390.1560.1660.1510.1070.2700.1930.1690.1830.1770.1870.1560.1640.1390.3751.0000.1370.0000.0820.2260.0430.0000.0830.1160.1520.1490.0930.0000.0270.0000.0500.1130.1050.090
securité_dans_espace_public_q160.0220.0470.0550.0290.0690.0430.0000.0000.0000.0000.0000.0000.0000.0850.1140.0000.0710.0860.0130.0950.0940.0800.0800.0710.0330.0900.0630.0530.0180.0590.0410.0840.0770.0580.0000.1371.0001.0000.0760.2080.0000.0330.0580.0480.0890.1100.0880.0690.0450.0210.0150.1150.0640.034
securité_dans_espace_public_q180.1680.0000.2740.0000.1440.0000.0000.0000.0000.0000.2700.0570.1560.0000.2030.0000.0000.2060.0000.1320.0000.0000.0000.0000.0400.0000.0000.0000.1120.0000.0970.0000.1140.0850.0000.0001.0001.0000.2680.0000.2140.1320.0000.0000.0690.0000.1430.0000.0000.0000.0000.0000.0000.235
participation_citoyenne_q190.0000.0000.0000.0000.0000.0000.0000.0000.0350.0480.0210.0870.1390.0390.0280.0000.1140.0800.0520.0660.0350.0130.0000.0470.0000.0000.0470.0000.0000.0000.0000.0610.0630.0650.0080.0820.0760.2681.0000.0000.0000.0560.0700.0000.0370.0000.0960.0390.0240.0100.0000.0000.1160.136
participation_citoyenne_q200.0000.0480.0000.0890.0000.0000.0000.0000.0810.2480.0880.0570.0000.2130.3720.1350.2440.1230.0000.1090.1070.0830.1430.0180.0420.2170.1540.0620.0510.0000.1220.0680.1340.1640.0000.2260.2080.0000.0001.0000.0790.1520.0670.2190.2310.0000.1020.0000.0820.0000.1190.2480.0270.000
profil_q250.2160.0590.0000.0240.0380.0000.0290.0000.0520.0440.0260.0650.0370.0510.0850.0930.0540.1130.0940.1210.0400.0330.0230.0000.0690.0000.0910.0720.0630.0820.0790.0760.0560.0460.1430.0430.0000.2140.0000.0791.0000.1140.1220.0490.0880.0820.0390.0360.0360.0790.0460.0600.1010.284
profil_q260.0300.0600.0100.0000.0550.0260.0340.0000.0000.0250.0590.0000.0000.0690.0310.0830.0420.0700.1190.0310.0450.0730.0680.1210.0000.0110.0000.0420.0660.0510.0000.0420.0190.0000.0000.0000.0330.1320.0560.1520.1141.0000.2880.0380.0240.0540.1150.0660.0320.0000.0940.1430.0590.000
profil_q270.0690.0200.0000.0390.0580.0000.0540.0000.0180.0060.0410.0000.0420.0660.1210.1500.0450.0810.1030.1510.0690.1060.1150.0870.1010.1260.0570.0670.0430.0680.0310.0430.0160.0260.1400.0830.0580.0000.0700.0670.1220.2881.0000.1230.1330.1250.2090.0000.1240.0750.1140.1550.0000.031
profil_q280.0790.0360.0410.0440.0700.0500.0260.0080.0000.0470.0460.0780.0570.0610.2050.0680.1290.1710.1300.1630.0500.1040.1030.1030.0460.1120.2110.1100.1150.1490.1320.0950.0750.1160.2890.1160.0480.0000.0000.2190.0490.0380.1231.0000.3940.3890.0500.0370.0000.0270.0070.1100.1060.000
profil_q290.1360.0640.0000.0350.0660.0520.0000.0000.0550.1150.0000.0000.0360.1120.2910.1230.1130.1900.1080.1780.0580.0920.0860.1030.0930.1870.1910.1990.1820.1770.1670.1480.0660.0890.1260.1520.0890.0690.0370.2310.0880.0240.1330.3941.0000.3270.1210.1290.0700.0640.0320.1620.1310.000
profil_q300.0660.0000.0000.0180.0500.0000.0330.0360.0400.0400.0630.0790.0600.0910.1870.1060.1090.1330.1060.1360.0660.1120.0940.1290.0860.1090.1990.1590.1520.1760.1450.1420.0950.1280.2870.1490.1100.0000.0000.0000.0820.0540.1250.3890.3271.0000.1180.1260.0650.1160.0650.0850.1040.004
profil_q310.0500.0260.0100.0000.0500.0220.0180.0000.0510.0000.0560.0440.0470.0470.0670.0470.0520.1110.0560.0460.0320.0890.0990.0400.0630.0700.0000.0330.0000.0260.0000.0490.0330.0000.0450.0930.0880.1430.0960.1020.0390.1150.2090.0500.1210.1181.0000.0000.0000.0000.1130.1440.0180.000
profil_q320.0530.0420.0000.0380.0490.0000.0140.0270.0250.0000.0390.0920.0460.0460.1230.0530.0930.1010.0720.1230.0000.0350.0530.0000.0650.0000.1040.1310.1160.1270.1110.0840.0000.0000.0420.0000.0690.0000.0390.0000.0360.0660.0000.0370.1290.1260.0001.0000.2690.3690.1210.0460.0450.000
profil_q330.0000.0000.0920.0000.0000.0680.0670.0000.0870.0000.0670.0490.0000.0950.1120.0380.0900.0890.0270.1500.0750.0730.1170.0640.0850.0720.0800.0790.0000.0890.0730.0000.0540.0490.0140.0270.0450.0000.0240.0820.0360.0320.1240.0000.0700.0650.0000.2691.0000.4870.2600.0760.0490.000
profil_q340.0000.0000.0170.0000.0000.0000.0470.0470.0320.0000.0000.0000.0700.1100.1060.0350.1050.1270.0590.1080.0220.0000.0220.0160.0480.0650.1080.1130.0000.1170.0850.0000.0740.1050.0000.0000.0210.0000.0100.0000.0790.0000.0750.0270.0640.1160.0000.3690.4871.0000.2670.0590.0550.000
profil_q350.0440.0000.0590.0000.0440.0840.0000.0000.0000.0410.0000.0000.0380.0510.0660.0000.0000.0320.0000.0150.0000.0260.0000.0000.0000.0560.0490.0000.0000.0000.0000.0000.0680.0560.0320.0500.0150.0000.0000.1190.0460.0940.1140.0070.0320.0650.1130.1210.2600.2671.0000.0480.0090.000
profil_q370.0000.0000.0160.0060.0420.0270.0330.0000.0450.0000.0000.0410.0600.0410.1530.1300.1050.1100.0500.1530.1020.0650.0750.0730.0660.1060.0920.0790.1080.1080.1000.1060.0590.0780.1610.1130.1150.0000.0000.2480.0600.1430.1550.1100.1620.0850.1440.0460.0760.0590.0481.0000.0570.000
interet_participer_groupe_discussion_q380.0620.0000.0000.0560.0220.0490.0580.0000.0640.0810.0710.0820.0770.0980.1420.0640.1310.1210.0800.1120.0000.1030.0670.0580.0070.0580.1140.1510.1530.1600.1540.1590.1020.0950.0830.1050.0640.0000.1160.0270.1010.0590.0000.1060.1310.1040.0180.0450.0490.0550.0090.0571.0000.000
interet_participer_groupe_discussion_q400.0000.1310.0280.0940.0000.0300.1290.0160.1060.1140.0460.0620.1040.0000.1050.0720.0270.1180.0830.0590.0530.0560.0880.0430.0000.1180.1370.0650.0390.1540.1630.0850.0920.0610.1060.0900.0340.2350.1360.0000.2840.0000.0310.0000.0000.0040.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-06-18T04:17:55.164669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-06-18T04:17:56.441682image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-06-18T04:18:00.070497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

idacces_services _ Ville_q1acces_services _ Ville_q2_1acces_services _ Ville_q2_2acces_services _ Ville_q2_3acces_services _ Ville_q2_4acces_services _ Ville_q2_5acces_services _ Ville_q2_6acces_services _ Ville_q2_7acces_services _ Ville_q2_8acces_services _ Ville_q3acces_services _ Ville_q4acces_services _ Ville_q5acces_services _ Ville_q6_1acces_services _ Ville_q6_2acces_services _ Ville_q6_3acces_services _ Ville_q6_4acces_services _ Ville_q6_5acces_services _ Ville_q6_6acces_services _ Ville_q6_7acces_services _ Ville_q7_1acces_services _ Ville_q7_2acces_services _ Ville_q7_3acces_services _ Ville_q7_4acces_services _ Ville_q7_5acces_services _ Ville_q8_1acces_services _ Ville_q8_2acces_services _ Ville_q8_3acces_services _ Ville_q8_4acces_services _ Ville_q8_5acces_services _ Ville_q9milieu_et_qualite_ de_vie_q10_1milieu_et_qualite_de_vie_q10_2milieu_et_qualite_ de_vie_q10_3milieu_et_qualite_de_vie_q10_4milieu_et_qualite_de_vie_q10_5milieu_et_qualite_de_vie_q10_6milieu_et_qualite_de_vie_q10_7milieu_et_qualite_de_vie_q10_8milieu_et_qualite_de_vie_q10_9milieu_et_qualite_de_vie_q11_1milieu_et_qualite_de_vie_q11_2milieu_et_qualite_de_vie_q11_3milieu_et_qualite_de_vie_q11_4milieu_et_qualite_de_vie_q11_5milieu_et_qualité_de_vie_q11_6milieu_et_qualite_de_vie_q11_7milieu_et_qualite_de_vie_q11_8milieu_et_qualite_de_vie_q12securité_dans_espace_public_q13securité_dans_espace_public_q14_1securité_dans_espace_public_q14_2securité_dans_espace_public_q14_3securité_dans_espace_public_q14_4securité_dans_espace_public_q14_5securité_dans_espace_public_q14_6securité_dans_espace_public_q14_7securité_dans_espace_public_q14_8securité_dans_espace_public_q14_9securité_dans_espace_public_q14_10securité_dans_espace_public_q14_11securité_dans_espace_public_q15_1securité_dans_espace_public_q15_2securité_dans_espace_public_q15_3securité_dans_espace_public_q15_4securité_dans_espace_public_q15_5securité_dans_espace_public_q15_6securité_dans_espace_public_q15_7securité_dans_espace_public_q15_8securité_dans_espace_public_q15_9securité_dans_espace_public_q16securité_dans_espace_public_q17_1securité_dans_espace_public_q17_2securité_dans_espace_public_q17_3securité_dans_espace_public_q17_4securité_dans_espace_public_q17_5securité_dans_espace_public_q17_6securité_dans_espace_public_q17_7securité_dans_espace_public_q17_8securité_dans_espace_public_q17_9securité_dans_espace_public_q18participation_citoyenne_q19participation_citoyenne_q20participation_citoyenne_q21_1participation_citoyenne_q21_2participation_citoyenne_q21_3participation_citoyenne_q21_4participation_citoyenne_q21_5participation_citoyenne_q21_6participation_citoyenne_q21_7piste_action_q22_1piste_action_q22_2piste_action_q22_3piste_action_q22_4piste_action_q22_5piste_action_q22_6piste_action_q22_7piste_action_q22_8piste_action_q22_9piste_action_q22_10piste_action_q23_1piste_action_q23_2piste_action_q23_3piste_action_q23_4piste_action_q23_5piste_action_q23_6piste_action_q23_7piste_action_q23_8profil_q25profil_q26profil_q27profil_q28profil_q29profil_q30profil_q31profil_q32profil_q33profil_q34profil_q35profil_q36profil_q37interet_participer_groupe_discussion_q38interet_participer_groupe_discussion_q40
01OuiBibliothèques municipalesNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNDe une à trois fois par moisPlutôt en accordPlutôt en accordBibliothèques municipalesBureaux Accès MontréalRéseau Accès culture ou Maisons de la cultureNaNNaNNaNLigne téléphonique 311OuiNonNonNonNonNonJe ne sais pasJe ne sais pasOuiOuiPlutôt en désaccordAu travailNaNNaNNaNÀ l'école ou dans une institution académiqueDans une bibliothèque municipaleNaNNaNNaNPlutôt en désaccordTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en accordPlutôt en accordNonOui, quelquefoisNaNNaNNaNNaNNaNNaNNaNMauvais service dans un commerce (magasin, restaurant ou café)NaNAutreNaNTransport en communNaNBibliothèque municipale ou Maison de la cultureNaNNaNNaNNaNCommerceNaNNonCe n’était pas un acte réprimé par la loiJ’ai pensé que c’était un acte trop banalNaNJe ne savais pas à qui porter plainteNaNNaNNaNJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelleCrainte que ma réalité ne soit pas comprise ou prise en considérationNaNManque de tempsNaNAccessibilité des lieux (ex.: accès à des toilettes non genrées)NaN10835647192NaNÀ travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationNaNNaNNaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Autres (veuillez préciser)4 à 10 ans15 à 24 ansNon-binaireOuiQueerUniversitaire - 1er cycleAnglaisNonNonNonH2J80 000 $ à 99 999 $NonNaN
12OuiBibliothèques municipalesBureaux Accès MontréalBureaux Accès culture ou Maisons de la cultureBureaux Accès culture ou Maisons de la cultureCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNLigne téléphonique 311Une fois par semaine ou plusPlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNNonOuiOuiOuiNonOuiNonOuiNonOuiPlutôt en désaccordAu travailDans la recherche d'un logementDans la recherche d'un emploiNaNÀ l'école ou dans une institution académiqueNaNNaNNaNNaNTout à fait en accordPlutôt en désaccordTout à fait en désaccordPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en accordPlutôt en accordNonOui, souventHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)CyberintimidationAgression physique (ex.: geste portant atteinte à l’intégrité physique)Agression sexuelle (ex.: acte sexuel non consenti, avec ou sans violence)Menace de violence physiqueNaNNaNRegard insistantNaNNaNTransport en communNaNNaNNaNÉvénement extérieurRue ou ruelleParc ou terrain de sportsNaNSur l'internet (ex.: Facebook, courriels, etc)OuiNaNNaNNaNNaNNaNNaNNaNNaNNaNAssez adéquatNonNaNCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelleNaNNaNNaNManque de confiance dans le processusNaNNaN68419735102NaNNaNNaNÀ travers des événements soutenus par la VilleNaNNaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNPar le biais d’un organisme ou d’une associationPlus de 20 ans45 à 54 ansFemmeOuiLesbienneCollégialFrançaisNonNonNonH3K15 000 $ à 19 999 $NonNaN
23OuiBibliothèques municipalesNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNNaNUne fois par semaine ou plusPlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasOuiOuiNonOuiNonNonNonNonNonTout à fait en accordAu travailNaNNaNNaNNaNNaNNaNNaNNaNPlutôt en désaccordPlutôt en désaccordPlutôt en accordPlutôt en accordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en accordOuiOui, rarementHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNJ’ai eu peur des représaillesNaNNaNNaNJ’ai pensé que ce serait sans effetJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNNaNCrainte que ma réalité ne soit pas comprise ou prise en considérationNaNManque de tempsNaNNaNNaN24936810517NaNÀ travers le nom des rues, des parcs ou des espaces publicsNaNÀ travers des événements soutenus par la VilleNaNNaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNPar une personne de mon entourage11 à 20 ans25 à 34 ansFemmeJe préfère ne pas répondreBisexuelleUniversitaire - 1er cycleAnglaisOuiOuiNonH2K60 000 $ à 79 999 $NonNaN
34OuiBibliothèques municipalesNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsJardins communautairesNaNUne fois par semaine ou plusPlutôt en accordPlutôt en accordNaNBureaux Accès MontréalRéseau Accès culture ou Maisons de la cultureCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsJardins communautairesNaNJe ne sais pasNonNonOuiNonJe ne sais pasNonJe ne sais pasNonNonPlutôt en désaccordAu travailNaNDans la recherche d'un emploiDans les transports en communNaNDans une bibliothèque municipaleDans la recherche d'un service communautaireAutreNaNPlutôt en désaccordTout à fait en désaccordPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en accordPlutôt en désaccordNonOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)CyberintimidationAgression physique (ex.: geste portant atteinte à l’intégrité physique)NaNMenace de violence physiqueNaNMauvais service dans un commerce (magasin, restaurant ou café)Regard insistantNaNNaNNaNNaNBibliothèque municipale ou Maison de la cultureNaNÉvénement extérieurNaNNaNCommerceNaNNonNaNNaNJ’ai eu peur des représaillesNaNNaNNaNJ’ai pensé que ce serait sans effetJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelleCrainte que ma réalité ne soit pas comprise ou prise en considérationNaNManque de tempsManque de confiance dans le processusAccessibilité des lieux (ex.: accès à des toilettes non genrées)NaN10238647951NaNNaNÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNPar une personne de mon entouragePlus de 20 ans25 à 34 ansFemmeOuiLesbienneUniversitaire - 1er cycleAnglaisNonOuiNonJe n’ai pas de domicile fixe10 000 $ à 14 999 $NonNaN
45OuiBibliothèques municipalesNaNBureaux Accès culture ou Maisons de la cultureBureaux Accès culture ou Maisons de la cultureNaNRéseau des parcs de quartier et grands parcsNaNLigne téléphonique 311Quelques fois par annéePlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiNonOuiNonNonNonNonNonPlutôt en accordNaNNaNNaNDans les transports en communNaNNaNNaNNaNNaNTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en accordPlutôt en accordPlutôt en désaccordPlutôt en accordPlutôt en désaccordNonOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)NaNCyberintimidationNaNNaNNaNNaNMauvais service dans un commerce (magasin, restaurant ou café)Regard insistantNaNNaNTransport en communNaNNaNNaNNaNRue ou ruelleParc ou terrain de sportsNaNSur l'internet (ex.: Facebook, courriels, etc)Je préfère ne pas répondreNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNNaNManque de tempsNaNNaNNaN26135481097À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Invitation de la Ville reçue par courrielPlus de 20 ans55 à 64 ansHommeNonGaieUniversitaire - 1er cycleFrançaisNonNonNonH1V100 000 $ à 149,999 $OuiNon
56OuiBibliothèques municipalesNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsJardins communautairesNaNQuelques fois par annéePlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasJe ne sais pasOuiOuiOuiJe ne sais pasJe ne sais pasOuiNonNonPlutôt en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasPlutôt en accordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordNonOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)NaNNaNNaNNaNNaNNaNRegard insistantNaNNaNTransport en communNaNNaNNaNÉvénement extérieurRue ou ruelleNaNNaNNaNNonCe n’était pas un acte réprimé par la loiNaNJ’ai eu peur des représaillesNaNNaNNaNJ’ai pensé que ce serait sans effetJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNCrainte de subir un traitement défavorable ou différencié en raison de mon identité et expression de genre ou de mon orientation sexuelleCrainte que ma réalité ne soit pas comprise ou prise en considérationNaNManque de tempsManque de confiance dans le processusNaNNaN57110829463À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNSite web de la VillePlus de 20 ans15 à 24 ansFemmeNonLesbienneCollégialFrançaisOuiOuiOuih1p60 000 $ à 79 999 $OuiNon
67OuiNaNBureaux Accès MontréalNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)NaNNaNLigne téléphonique 311Quelques fois par annéePlutôt en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiNonOuiNonNonNonOuiNonTout à fait en accordNaNNaNNaNNaNNaNNaNNaNAutreNaNPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordNonOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)CyberintimidationNaNNaNNaNNaNNaNRegard insistantNaNNaNNaNNaNNaNNaNÉvénement extérieurNaNNaNNaNSur l'internet (ex.: Facebook, courriels, etc)Je préfère ne pas répondreNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNOuiNonNaNNaNNaNNaNManque de confiance dans le processusNaNNaN61098574231À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsNaNNaNNaNNaNNaNEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Site web de la VillePlus de 20 ans35 à 44 ansFemmeNonLesbienneUniversitaire - cycles supérieursFrançaisNonNonNonH1L30 000 $ à 39 999 $NonNaN
78OuiNaNNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNMoins d'une fois par annéePlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasOuiJe ne sais pasNonNonJe ne sais pasNonJe ne sais pasJe ne sais pasJe ne sais pasPlutôt en accordAu travailNaNNaNDans les transports en communÀ l'école ou dans une institution académiqueNaNNaNNaNNaNPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en accordNonOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)NaNNaNNaNNaNNaNNaNRegard insistantNaNNaNTransport en communNaNNaNNaNNaNRue ou ruelleNaNCommerceNaNNonCe n’était pas un acte réprimé par la loiJ’ai pensé que c’était un acte trop banalJ’ai eu peur des représaillesJe ne savais pas à qui porter plainteNaNNaNNaNNaNNaNNaNNonNaNNaNCrainte que ma réalité ne soit pas comprise ou prise en considérationHoraires inadéquatsNaNNaNNaNNaN49310857162À travers l’art (mural, festival, etc.)NaNNaNÀ travers des événements soutenus par la VilleNaNNaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Par une personne de mon entourage1 à 3 ans15 à 24 ansNon-binaireOuiQueerSecondaireAnglaisOuiOuiNonh2w5 000 $ à 9 999 $NonNaN
89OuiBibliothèques municipalesNaNNaNNaNNaNNaNJardins communautairesNaNDe une à trois fois par moisTout à fait en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiOuiOuiNonNonNonNonNonTout à fait en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasTout à fait en accordTout à fait en accordTout à fait en accordTout à fait en accordTout à fait en accordTout à fait en accordTout à fait en accordTout à fait en accordOuiNon, jamaisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNNaNNaNNaNNaNAucun31076824195À travers l’art (mural, festival, etc.)NaNNaNNaNNaNNaNNaNNaNSite web de la Ville4 à 10 ans35 à 44 ansNon-binaireJe préfère ne pas répondreEn questionnementUniversitaire - cycles supérieursFrançaisNonNonNonH2S80 000 $ à 99 999 $NonNaN
910OuiNaNNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNQuelques fois par annéePlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiOuiOuiJe ne sais pasNonOuiOuiOuiPlutôt en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordOuiOui, quelquefoisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNNaNNaNNaNNaNAucun71061824539NaNNaNÀ travers des campagnes d’information et de sensibilisationNaNNaNNaNNaNNaNPar une personne de mon entouragePlus de 20 ans55 à 64 ansFemmeNonJe préfère ne pas répondreUniversitaire - cycles supérieursFrançaisNonNonNonH3S150 000 $ et plusNonNaN
idacces_services _ Ville_q1acces_services _ Ville_q2_1acces_services _ Ville_q2_2acces_services _ Ville_q2_3acces_services _ Ville_q2_4acces_services _ Ville_q2_5acces_services _ Ville_q2_6acces_services _ Ville_q2_7acces_services _ Ville_q2_8acces_services _ Ville_q3acces_services _ Ville_q4acces_services _ Ville_q5acces_services _ Ville_q6_1acces_services _ Ville_q6_2acces_services _ Ville_q6_3acces_services _ Ville_q6_4acces_services _ Ville_q6_5acces_services _ Ville_q6_6acces_services _ Ville_q6_7acces_services _ Ville_q7_1acces_services _ Ville_q7_2acces_services _ Ville_q7_3acces_services _ Ville_q7_4acces_services _ Ville_q7_5acces_services _ Ville_q8_1acces_services _ Ville_q8_2acces_services _ Ville_q8_3acces_services _ Ville_q8_4acces_services _ Ville_q8_5acces_services _ Ville_q9milieu_et_qualite_ de_vie_q10_1milieu_et_qualite_de_vie_q10_2milieu_et_qualite_ de_vie_q10_3milieu_et_qualite_de_vie_q10_4milieu_et_qualite_de_vie_q10_5milieu_et_qualite_de_vie_q10_6milieu_et_qualite_de_vie_q10_7milieu_et_qualite_de_vie_q10_8milieu_et_qualite_de_vie_q10_9milieu_et_qualite_de_vie_q11_1milieu_et_qualite_de_vie_q11_2milieu_et_qualite_de_vie_q11_3milieu_et_qualite_de_vie_q11_4milieu_et_qualite_de_vie_q11_5milieu_et_qualité_de_vie_q11_6milieu_et_qualite_de_vie_q11_7milieu_et_qualite_de_vie_q11_8milieu_et_qualite_de_vie_q12securité_dans_espace_public_q13securité_dans_espace_public_q14_1securité_dans_espace_public_q14_2securité_dans_espace_public_q14_3securité_dans_espace_public_q14_4securité_dans_espace_public_q14_5securité_dans_espace_public_q14_6securité_dans_espace_public_q14_7securité_dans_espace_public_q14_8securité_dans_espace_public_q14_9securité_dans_espace_public_q14_10securité_dans_espace_public_q14_11securité_dans_espace_public_q15_1securité_dans_espace_public_q15_2securité_dans_espace_public_q15_3securité_dans_espace_public_q15_4securité_dans_espace_public_q15_5securité_dans_espace_public_q15_6securité_dans_espace_public_q15_7securité_dans_espace_public_q15_8securité_dans_espace_public_q15_9securité_dans_espace_public_q16securité_dans_espace_public_q17_1securité_dans_espace_public_q17_2securité_dans_espace_public_q17_3securité_dans_espace_public_q17_4securité_dans_espace_public_q17_5securité_dans_espace_public_q17_6securité_dans_espace_public_q17_7securité_dans_espace_public_q17_8securité_dans_espace_public_q17_9securité_dans_espace_public_q18participation_citoyenne_q19participation_citoyenne_q20participation_citoyenne_q21_1participation_citoyenne_q21_2participation_citoyenne_q21_3participation_citoyenne_q21_4participation_citoyenne_q21_5participation_citoyenne_q21_6participation_citoyenne_q21_7piste_action_q22_1piste_action_q22_2piste_action_q22_3piste_action_q22_4piste_action_q22_5piste_action_q22_6piste_action_q22_7piste_action_q22_8piste_action_q22_9piste_action_q22_10piste_action_q23_1piste_action_q23_2piste_action_q23_3piste_action_q23_4piste_action_q23_5piste_action_q23_6piste_action_q23_7piste_action_q23_8profil_q25profil_q26profil_q27profil_q28profil_q29profil_q30profil_q31profil_q32profil_q33profil_q34profil_q35profil_q36profil_q37interet_participer_groupe_discussion_q38interet_participer_groupe_discussion_q40
14381439OuiNaNBureaux Accès MontréalNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNQuelques fois par annéeTout à fait en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiOuiOuiNonNonNonNonNonTout à fait en accordNaNNaNNaNNaNNaNNaNNaNAutreNaNPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordOuiNon, jamaisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNHoraires inadéquatsManque de tempsNaNNaNNaN41106523897À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Autres (veuillez préciser)4 à 10 ans25 à 34 ansHommeNonGaieUniversitaire - cycles supérieursFrançaisNonNonNonh2h150 000 $ et plusNonNaN
14391440NonNaNNaNNaNNaNNaNNaNNaNNaNQuelques fois par annéePlutôt en accordPlutôt en accordNaNNaNNaNCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)NaNNaNNaNOuiOuiNonNonOuiNonNonJe ne sais pasJe ne sais pasNonPlutôt en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en accordPlutôt en accordNonNon, jamaisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNCrainte que ma réalité ne soit pas comprise ou prise en considérationNaNManque de tempsManque de confiance dans le processusAccessibilité des lieux (ex.: accès à des toilettes non genrées)NaN11082365497NaNNaNNaNÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)NaNNaNEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Page Facebook de la Ville1 à 3 ans35 à 44 ansHommeOuiHétérosexuelleCollégialFrançaisNonNonNonH1X80 000 $ à 99 999 $NonNaN
14401441OuiNaNBureaux Accès MontréalNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNQuelques fois par annéePlutôt en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiOuiOuiNonOuiNonNonOuiPlutôt en accordNaNNaNNaNDans les transports en communNaNNaNNaNNaNNaNPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordOuiOui, rarementHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)NaNNaNNaNNaNNaNNaNRegard insistantNaNNaNTransport en communNaNNaNNaNÉvénement extérieurNaNNaNNaNNaNNonNaNNaNNaNNaNNaNNaNJ’ai pensé que ce serait sans effetJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNNaNNaNHoraires inadéquatsManque de tempsNaNNaNNaN46517289103NaNNaNÀ travers des campagnes d’information et de sensibilisationNaNNaNÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Page Facebook de la VillePlus de 20 ans35 à 44 ansHommeNonGaieUniversitaire - 1er cycleFrançaisNonNonNonh1l80 000 $ à 99 999 $NonNaN
14411442OuiBibliothèques municipalesNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsJardins communautairesLigne téléphonique 311Une fois par semaine ou plusPlutôt en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNNonOuiOuiOuiNonNonNonNonNonJe ne sais pasPlutôt en accordNaNNaNNaNDans les transports en communNaNNaNNaNNaNNaNPlutôt en accordPlutôt en accordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en désaccordPlutôt en accordPlutôt en accordOuiOui, quelquefoisHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)NaNCyberintimidationNaNNaNNaNNaNNaNRegard insistantNaNNaNTransport en communNaNNaNNaNÉvénement extérieurRue ou ruelleNaNNaNSur l'internet (ex.: Facebook, courriels, etc)NonCe n’était pas un acte réprimé par la loiNaNNaNJe ne savais pas à qui porter plainteNaNJe ne voulais pas devoir faire mon «coming out»NaNNaNNaNNaNOuiNonNaNNaNHoraires inadéquatsManque de tempsNaNNaNNaN12346571098À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+TwitterPlus de 20 ans15 à 24 ansHommeNonGaieCollégialAnglaisOuiOuiNonH4p30 000 $ à 39 999 $OuiNon
14421443OuiNaNNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNLigne téléphonique 311De une à trois fois par moisPlutôt en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasOuiOuiJe ne sais pasJe ne sais pasJe ne sais pasNonNonJe ne sais pasJe ne sais pasPlutôt en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasPlutôt en accordPlutôt en accordPlutôt en accordTout à fait en accordPlutôt en accordTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordNonOui, rarementNaNNaNNaNNaNNaNNaNNaNNaNRegard insistantNaNNaNTransport en communNaNNaNCentre sportif ou communautaireNaNRue ou ruelleParc ou terrain de sportsCommerceNaNNonNaNNaNNaNNaNNaNNaNNaNJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNNonNaNNaNNaNNaNNaNManque de confiance dans le processusNaNNaN14671038952NaNNaNÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleNaNÀ travers une plus grande représentation municipale aux événements des communautés LGBTQ+NaNNaNPage Facebook de la VillePlus de 20 ans55 à 64 ansHommeNonGaieUniversitaire - 1er cycleFrançaisNonNonNonH1V80 000 $ à 99 999 $NonNaN
14431444OuiBibliothèques municipalesNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)NaNNaNNaNQuelques fois par annéeTout à fait en accordPlutôt en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasJe ne sais pasOuiJe ne sais pasOuiJe ne sais pasNonNonNonOuiPlutôt en accordNaNNaNNaNNaNNaNNaNNaNNaNNe s'applique pasTout à fait en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordOuiOui, rarementNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNHoraires inadéquatsManque de tempsNaNNaNNaN12345687910NaNÀ travers le nom des rues, des parcs ou des espaces publicsNaNNaNÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)NaNNaNNaNPage Facebook de la Ville1 à 3 ans15 à 24 ansHommeNonGaieCollégialFrançaisNonNonNonH1M80 000 $ à 99 999 $NonNaN
14441445OuiNaNNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNNaNDe une à trois fois par moisTout à fait en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiOuiOuiJe ne sais pasNonOuiNonJe ne sais pasTout à fait en accordAu travailNaNNaNNaNNaNNaNNaNNaNNaNPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en désaccordPlutôt en accordPlutôt en désaccordPlutôt en accordPlutôt en accordOuiNon, jamaisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNNaNNaNManque de confiance dans le processusNaNNaN18104567392À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)NaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNPage Facebook de la Ville11 à 20 ans25 à 34 ansHommeNonJe préfère ne pas répondreUniversitaire - cycles supérieursFrançaisNonNonNonH3C150 000 $ et plusNonNaN
14451446OuiNaNNaNNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNLigne téléphonique 311Une fois par semaine ou plusPlutôt en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNJe ne sais pasJe ne sais pasJe ne sais pasNonJe ne sais pasJe ne sais pasNonNonJe ne sais pasJe ne sais pasTout à fait en accordAu travailNaNNaNNaNNaNNaNNaNNaNNaNPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordPlutôt en accordNonOui, quelquefoisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNRien de tout cela ne m’est arrivé dans les vingt quatre derniers moisNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNHoraires inadéquatsManque de tempsManque de confiance dans le processusNaNNaN52691037481À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsÀ travers des campagnes d’information et de sensibilisationÀ travers des événements soutenus par la VilleÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)À travers une plus grande représentation municipale aux événements des communautés LGBTQ+En invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNTwitter11 à 20 ans35 à 44 ansHommeNonGaieUniversitaire - cycles supérieursAnglaisNonNonNonH2L150 000 $ et plusNonNaN
14461447OuiNaNBureaux Accès MontréalNaNNaNCentres sportifs et de loisirs (piscines, terrains de tennis, etc.)Réseau des parcs de quartier et grands parcsNaNNaNQuelques fois par annéePlutôt en accordPlutôt en accordNaNBureaux Accès MontréalNaNCentres sportifs et de loisirs (piscine, terrains de tennis, etc.)NaNNaNNaNNonNonNonNonNonJe ne sais pasJe ne sais pasJe ne sais pasJe ne sais pasJe ne sais pasPlutôt en accordNaNDans la recherche d'un logementDans la recherche d'un emploiDans les transports en communÀ l'école ou dans une institution académiqueNaNNaNNaNNaNTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordTout à fait en désaccordTout à fait en désaccordTout à fait en désaccordPlutôt en désaccordPlutôt en désaccordNonOui, souventHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)Avance sexuelle non désirée (ex.: avance verbale ou proposition insistante à caractère sexuel non désirée)CyberintimidationNaNNaNNaNNaNNaNRegard insistantAutreNaNTransport en communNaNNaNNaNNaNRue ou ruelleNaNCommerceSur l'internet (ex.: Facebook, courriels, etc)NonNaNNaNJ’ai eu peur des représaillesJe ne savais pas à qui porter plainteJe ne voulais pas revivre le momentNaNNaNJ’ai pensé que ce serait trop compliqué / me demanderait trop de tempsNaNNaNOuiNonNaNCrainte que ma réalité ne soit pas comprise ou prise en considérationHoraires inadéquatsManque de tempsManque de confiance dans le processusAccessibilité des lieux (ex.: accès à des toilettes non genrées)NaN76534892101NaNNaNÀ travers des campagnes d’information et de sensibilisationNaNÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)NaNNaNEn identifiant une personne de la Ville de Montréal chargée de porter le dossier des enjeux LGBTQ+Page Facebook de la VillePlus de 20 ans25 à 34 ansHommeOuiBisexuelleUniversitaire - 1er cycleAnglaisOuiNonNonH2R60 000 $ à 79 999 $OuiNon
14471448OuiNaNNaNNaNNaNNaNRéseau des parcs de quartier et grands parcsNaNNaNDe une à trois fois par moisPlutôt en accordTout à fait en désaccordNaNNaNNaNNaNNaNNaNNaNOuiOuiOuiNonOuiNonNonNonOuiNonTout à fait en accordNaNNaNNaNNaNNaNNaNNaNAutreNaNPlutôt en accordPlutôt en accordPlutôt en accordTout à fait en accordPlutôt en accordPlutôt en désaccordPlutôt en accordTout à fait en accordOuiOui, rarementHarcèlement verbal (ex.: insulte, blague de mauvais goût, intimidation)NaNNaNNaNNaNMenace de violence physiqueNaNNaNRegard insistantNaNNaNNaNNaNNaNNaNNaNRue ou ruelleParc ou terrain de sportsNaNNaNNonCe n’était pas un acte réprimé par la loiNaNNaNNaNNaNNaNNaNNaNNaNNaNNonNaNNaNNaNHoraires inadéquatsManque de tempsNaNNaNNaN31074528691À travers l’art (mural, festival, etc.)À travers le nom des rues, des parcs ou des espaces publicsNaNNaNÀ travers des communications plus inclusives des communautés LGBTQ+ (publications web, dépliants, etc.)NaNEn invitant les organismes LGBTQ+ aux événements de la Ville de MontréalNaNTwitter4 à 10 ans25 à 34 ansHommeNonGaieUniversitaire - 1er cycleFrançaisNonNonNonH2L100 000 $ à 149,999 $OuiNon